SAFETY CLIMATE ASSIGNMENT ( READ THE ARTICLE AND AND ASWER THE QUESTIONS)

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Yueng-Hsiang (Emily) Huang, Ph.D., is a senior research scientist at Liberty Mutual Research Institute for Safety (LMRIS) in Hopkin- ton, MA. She holds a Ph.D. in Industrial-Organizational Psychology/ Systems Science from Portland State University. She conducts both laboratory and field research in areas such as occupational injury and accident prevention, and organizational culture and climate. She is a Fellow of the American Psychological Association and the Society for Industrial-Organizational Psychology. Huang is an associate editor of Accident Analysis and Prevention.

Susan Jeffries is a research specialist at LMRIS where she recruits companies as potential partners in research for field studies and serves as liaison between the institute and corporate safety profes- sionals in such initiatives. She conducts qualitative research through in-depth interviews and focus groups to investigate issues relating to safety in the trucking industry and other lone worker environments. Jeffries holds a B.S. in Marketing from Boston College.

George D. (Don) Tolbert, CSP, is technical director, organizational practices, with Liberty Mutual’s Risk Control Service department. His responsibilities include development of process and resources to support consulting services to help companies improve efficacy of safety management systems across all industries. Tolbert holds a B.S. from University of Georgia. He is a professional member of ASSE’s Georgia Chapter.

Marvin J. Dainoff, Ph.D., CPE, is director of the Center for Behav- ioral Sciences at LMRIS. He has research interests in workplace ergo- nomics and systems approaches to complex systems. He is a Fellow and past president of the Human Factors and Ergonomics Society, and director, emeritus, of the Board of Certification in Professional Er- gonomics. He is professor emeritus in the Department of Psychology and founding director of the Center for Ergonomic Research, Miami University, Oxford, OH.

In BrIef •This article discusses a study designed to better understand safety climate in the lone worker environ- ment and its potential impact on safety performance. •The authors developed and tested the validity of a generic safety climate sur- vey geared toward the lone working situation, then developed two safety climate surveys designed for trucking and utility workers. •The article presents the scientific integrity of the survey development process, and discusses the concepts of survey reliability and validity evidence. It also offers practical suggestions on how to implement surveys in the field.

Safety Management Peer-Reviewed

How Can You Measure It & Why Does It Matter?

By Yueng-Hsiang (Emily) Huang, Susan Jeffries, George D. (Don) Tolbert and Marvin J. Dainoff

J ane, a truck driver, is en route to an impor- tant customer site and

road conditions change—a crash, construction, a de- tour—resulting in heavy traffic. Unless she speeds, the delivery will be late. The driver knows she should ad- here to the speed limit, but the customer is waiting and the boss is expecting results. What does she do?

The pressure is on all utility crews to restore power for an important customer. Despite having already worked a reg- ular shift, Joe, a lineman feels obligated to stay on duty. He knows the company’s repu- tation is at stake and the boss

is being pressured, but exhaustion has set in and he cannot think straight. What does he do?

Every day, truck drivers, utility workers and oth- er lone workers encounter situations in which safe- ty conflicts with job demands. Because they work remotely, these individuals must often resolve the conflicts alone, without the direct support or input of supervisors or management. Liberty Mutual Re- search Institute for Safety (LMRIS) found that even for lone workers a company’s safety climate (em- ployees’ safety perceptions) is strongly associated with safety behaviors and injury outcomes.

Safety Climate In recent years, risk managers and safety di-

rectors have begun exploring organizational and psychosocial factors in the workplace to comple- ment traditional safety approaches (e.g., engineer- ing design, protective equipment, training). One prominent area being explored is safety climate, which was first introduced by Zohar (1980). Zohar defined safety climate as workers’ shared percep- tion of an organization’s policies, procedures and practices as they relate to the true/relative value and importance of safety within the organization

Safety Climate

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(Zohar, 1980). Safety climate reflects a company’s state of safety at a discrete point in time.

The number of scientific studies on the topic has rapidly increased in recent years, with emerg- ing evidence supporting safety climate as a robust predictor of safety outcomes (Christian, Bradley, Wallace, et al., 2009). In 2009, Zohar joined author Huang of LMRIS’s Center for Behavioral Sciences to launch an extensive safety climate research ini- tiative that continues today.

Safety Climate vs. Culture Safety climate is often confused with safety cul-

ture. In fact, these terms describe two related but somewhat different phenomena. Safety culture is de- scribed as shared norms, values and beliefs that set expectations for acceptable behavior within an orga- nization and are taught to new employees through socialization (i.e., the way we do things around here). On the other hand, safety climate refers to employ- ees’ shared perceptions of the true/relative priority of safety (i.e., how employees perceive the company’s commitment to safety as it is lived out, or not, ev- ery day). Research indicates that safety climate can be used to predict safety behavior and safety-related outcomes (e.g., incidents, injuries) in a wide variety of settings. While safety culture cannot be easily mea- sured directly, safety climate can serve as an indica- tor/measure of safety culture.

Importance of Safety Climate Safety climate can serve as a frame of reference

for developing clear expectations regarding em- ployees’ safety-related actions and the expected re- action from management. Thus, in a company with a high safety climate level, employees might per- ceive that they are encouraged to maintain good safety practices despite increased production pres- sure. Consequently, they behave safely. Employees usually develop these perceptions and expectations

by observing the actions of supervisors and managers. These perceptions are rein- forced by social interaction with coworkers, resulting in a kind of consensus re- garding the company’s true/ relative safety priorities (e.g., safety vs. productivity).

Perceptions at Different Management Levels

The question can then be raised: Who is the company? Is it the executives, my super- visor or my coworkers? Since organizational consistency throughout different levels of managers is a key aspect of climate, safety climate is best measured at different cascad- ing levels. Scientific research suggests that it is important to capture the employee’s

perceptions of his/her immediate supervisor with regard to safety, as well as his/her perceptions of the overall company or top management with re- gard to the value placed on safety. Safety climate researchers refer to employees’ perceptions of their immediate supervisors as group-level safety cli- mate, while their perceptions of top management are referred to as organization-level safety climate. A comprehensive safety climate study would in- clude questions regarding both levels.

The Safety Climate Lone Worker Study Safety climate research has typically focused on

traditional workplaces in which supervisors and employees share the same physical location. Zo- har and Luria (2005) gained industry acclaim with their development of a safety climate survey con- taining 32 questions, which laid the groundwork for measuring safety in organizations. This survey was generic in the sense that it was intended to apply to different types of industries and work settings. The LMRIS study team sought to expand on this research to examine the safety climate of lone work- ers. A lone worker is an employee who works alone and who performs an activity intended to be carried out in isolation from other workers, without close or direct supervision (Hughes & Ferrett, 2009).

Given that lone working is becoming increas- ingly prevalent across various industries (e.g., truck drivers, utility workers, teleworkers), it is important to conceptualize the effect of this work environ- ment on organizational climate emergence. Safety climate can be important for this unique popula- tion because it can act as a frame of reference that guides safety behavior. Employees receive cues from others within the company and formulate perceptions that may ultimately impact their own behavior. This was an opportunity to see how lone workers process these cues from afar and how they behave when no one is watching. With this goal ©i

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in mind, the LMRIS researchers developed a new safety climate survey with items applicable to all lone workers and two industry-specific surveys with additional content focused on truck drivers and electric utility workers.

Research Objectives The LMRIS study’s primary objective was to bet-

ter understand safety climate in the lone worker environment and its potential impact on safety performance. To accomplish this goal, the authors first developed and tested the validity of a generic safety climate survey geared toward lone workers. As a first step, researchers adapted 12 of the 32 items from the Zohar and Luria (2005) scale that would apply to lone workers. The second step in- volved expanding on this knowledge to develop two valid, reliable safety climate surveys designed specifically for truck drivers and for utility work- ers. These surveys would be more comprehensive, considering the specific attributes of these indus- tries. Each survey gathered information on the two levels noted: top management (organization-level) and immediate supervisors (group-level).

Scientific Integrity of the Surveys In this case, the survey measures the construct

of  safety climate and assesses the quality of the measuring process itself. How can one know whether the survey is measuring what it is intend- ed to measure? A person need not be a scientist to create a survey, hand it out to a group of people and analyze the responses. However, the respons- es may be difficult to interpret and may potentially be ambiguous (i.e., not reliable or valid). Therefore,

when a company plans to conduct a survey, either directly or through a consultant, it is important to carefully evaluate the evidence, specifically, the re- liability and validity of the scales.

Psychometric measurement is one aspect of the general field of measurement that also includes physical measurement (see “Psychometric Mea- sures” sidebar). For example, consider a familiar physical scale. Imagine that you are standing in front of two bathroom scales. Your true weight is 150 lb. You step on the first scale three times, resulting in the readings 150, 120 and 140 lb. You step on the second scale three times, resulting in the readings 172, 172 and 171 lb. The first scale gives inconsistent readings. Clearly, something is wrong with that scale’s mechanism, therefore it is not reliable. The second scale gives consistent readings that do not indicate your true weight. The scale may be incorrectly calibrated, therefore it is not valid. Simply put, a valid scale measures what it is supposed to measure. While the principles of reliability and validity apply to any measurement activity, psychometric methods are sets of scientific best practices that help to ensure that these sur- veys result in scales that can accurately measure psychological concepts such as safety climate.

Reliability Reliability, in scientific terms, is usually described

as the repeatability and consistency of a test. Vari- ous scientific methods assess whether a scale is reliable. For the purpose of safety climate scales, researchers examined the internal consistency reli- ability, which looks at the patterns of response from a single administration of a survey. This approach estimates what would happen if we split the survey response into two halves multiple times. The esti- mated average correlation between these halves is called the coefficient alpha, which is a measure of consistency. From a practical perspective, unless a measurement scale has a reasonable degree of reli- ability (coefficient alpha equal to at least 0.7) it is not useful for interpretation purposes.

Validity Validity signifies the strength of a test and

whether its results are accurate. Many different methods assess whether a scale is actually mea- suring what we think it should; for this study, re- searchers used three basic approaches.

1) Content validity indicates whether the con- tent of items actually corresponds to the underly- ing concept that the survey is supposed to measure (e.g., safety climate), and whether the meaning of each item is clear and intuitive. This is typically at- tained by careful review of potential items by field- based subject-matter experts.

2) Criterion-related validity is assessed by cor- relating individual scores on the measurement scale with some corresponding outcome (criterion) measure. Outcome measures can be collected at the same time as the survey (i.e., concurrent valid- ity) or at some time in the future (i.e., predictive va- lidity). For example, if we include a scale of safety

Psychometric Measures arising with the advent of psychology as a field of experimental

study in the late 19th century, psychometric methods are central to the scientific study of behavior and mental processes. some of the methods used in this study are (guilford, 1954; psychometric society, 2016): •Psychological scaling: originating in psychophysics, the

measurement of subjective perceptions by examining responses to stimuli using models established empirically.

1) reliability: consistent patterns in the measures obtained. 2) Validity: measurement of what is intended. •Correlation: a statistical method to determine the relation-

ship between two variables that results in a correlation coefficient (values ranging from -1 to +1). the further the coefficient is from zero, the stronger the relationship is between variables. a posi- tive correlation means that as the value of one variable increases, so does the value of the second variable. a negative correlation means that as the value of one variable increases, the value of the second variable decreases. •Regression: a statistical technique used to predict criterion

performance on the basis of predictor scores. regression permits the prediction of the score on one variable (the criterion) based on the score changes on another variable (the predictor). multiple regression allows prediction on the basis of multiple predictors. •Factor analysis: a statistical procedure for describing the

interrelationships among a number of scale items. Factor analysis tests these relationships and determines how items cluster into different dimensions/factors.

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behaviors when we measure safety climate, these behaviors can be considered outcome measures. In this case, each individual is reporting the likeli- hood of his/her specific safety-related actions. To the extent that a positive correlation exists between self-reports of carrying out these actions and safety climate, the safety climate scale has some degree of concurrent validity.

If we can collect actual incidents (e.g., injuries, near-hits) 6 months following the initial safety cli- mate survey, then correlate each person’s safety climate score with his/her incident score, we have a stronger argument. This is called predictive valid- ity since we can argue that safety climate predicts lagged safety outcomes (i.e., a sustaining predic- tive relationship between safety climate and safety outcomes). In practice, it is more difficult to col- lect outcome data 6 months later, so most studies rely on concurrent validity. However, the LMRIS team could collect both participants’ self-reported safety behaviors and objective incidences of acci- dents, injuries and near-hits, one concurrently and the other 6 months after survey implementation (Figure 1).

3) Factorial validity assesses how well the items cluster together into factors, which can relate to the underlying construct we are trying to measure. An advanced statistical procedure called factor analysis is used for this purpose. Survey designers gener- ate more items than will appear on the final sur- vey. Factor analysis is an effective method through which good items can be selected and bad items can be excluded, based on factor loadings.

These statistical methods may not be practical or feasible for everyone, but they are excellent tools to help researchers develop a scientific survey. In this case, it helped to ensure that the surveys being developed would result in a trustworthy scale for practitioners. It would benefit anyone considering implementation to inquire about the scientific re- liability and validity of a survey being considered.

Survey Process For the lone worker safety climate study, re-

searchers utilized scientific best practices to devel- op a procedure that was systematic and exhaustive. They wanted to ensure that the content of the sur- veys would reflect an organization’s state of safety, and be relevant to the participants in their respec- tive jobs. The process entailed several steps.

Information Gathering First, the project team conducted an extensive

literature search and review on trucking, utility and lone work for contextual background information. Team members talked with subject-matter experts in each industry to build on this knowledge. The team conducted in-depth interviews with 53 truck drivers and supervisors, and 38 utility workers to learn from lone workers about their jobs and what safety issues are important to them. Team mem- bers also spent several days in the field shadowing workers on the job and observing these safety is- sues in practice.

Question Development/Item Generation Raw items were generated to formulate potential

survey questions. Items were based on the infor- mation gathered from both the available literature and directly from workers and industry experts. Given the large number of participants and various issues that surfaced, a large number of initial items were generated. For example, for the trucking sur- vey, more than 100 initial items were developed; many overlapped in basic content, but it was im- portant to capture everything.

Cognitive Testing & Pilot Testing Once questions were developed, they had to be

tested. Researchers needed to make sure they ad- dressed issues that were meaningful to the workers as related to safety in their jobs. The researchers also wanted to ensure that the wording was clearly understood by respondents, and that the terms and phrasing were applicable to their industry. To accomplish this objective, the team conducted think-aloud cognitive interviews with 38 truck drivers and 45 utility workers. These interviews al- lowed researchers to examine the meaning of the survey responses (for clarification) and to observe respondents for potential issues (e.g., events such as long pauses, answers that are changed, indica- tions of confusion).

Based on this feedback, researchers revised or deleted some items, resulting in smaller, more re- fined sets of questions. Researchers pilot-tested the revised surveys with 64 truck drivers for one survey and 139 utility workers for the other to en- sure that the instructions and questions were clear and the overall survey administration was practical. The researchers refined the surveys again based on this feedback.

Implementation to Subsample The two revised surveys were then implemented

at the pilot companies in both industries, with 1,891 truck driver respondents and 1,560 utility work- ers. The researchers conducted exploratory factor analysis and coefficient alpha reliability to learn what the responses were, how the items may have grouped into themes, and whether these items made sense within the context of the organization.

Figure 1 Correlation Table of Safety Climate Scores & DOT records

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The final surveys included 12 items adapted from the original generic safety climate survey appropri- ate for lone workers, and additional items tailored to jobs in each of the two lone worker industries (28 items for trucking, 36 for utility). Incorporating industry-specific factors provides a stronger value, which makes these surveys a useful tool for the ap- propriate participants.

Implementation to Full Sample The final industry-specific safety climate surveys

were then implemented at seven additional truck- ing companies with 6,556 respondents and one additional utility company with 869 respondents. At this point, researchers ran confirmatory factor analysis on each to measure the validity of what was found with the two pilot companies, reinforc-

ing the grouping of potential themes for future analysis. This provided an excellent basis on which to offer these surveys to LMRIS risk control consul- tants to share with safety professionals and to the public at large for use in the field (Figure 2).

Results Study results showed that safety climate affects

safety behavior, even in the context of the lone work environment. It found that safety climate is a predictor of future injuries among these workers, substantiated by objective outcome measures. Re- searchers validated that the generic safety climate scale/survey was applicable to lone workers. They also found that the industry-specific surveys were even more predictive of future injuries than their generic counterparts (Huang, Zohar, Robertson, et al., 2013a, b).

Table 1 shows items contained in the lone work- er survey, and Figure 3 shows mean ratings from workers sampled in the studies by Huang, et al. (2013a, b). The circled items in Figure 3 represent the highest and lowest scoring elements accord- ing to the mean score statistic. Users of safety cli- mate survey findings value the insights provided by identifying high and low scoring items. This en- ables building on strengths to engage opportuni- ties. The highest and lowest mean scores in Figure 3 indicate that participating companies tend to do well, according to workers’ perceptions, in the area of safety training (organization-level item 4), but that management may not listen carefully enough to their ideas about safety (organization-level item 5). Regarding supervisors, results showed that in general workers felt that their supervisors do fairly well discussing with them how to improve safety (group-level item 1), but that they may sometimes ignore safety rules when work falls behind sched- ule (group-level item 5).

Survey Use in the Field More than ever, stake-

holders in safety are inter- e s t e d i n s u s t a i n a b l e a n d affordable risk-reduction strategies. In essence, an in- creased demand exists for safety process initiatives that are smarter, more lasting and produce higher returns. Sur- veys that combine science with efficient technology can diagnose the current state of an organization’s safety cli- mate and identify opportuni- ties for real improvements.

It would be counterpro- ductive for all concerned if a survey designed to measure safety climate were adminis- tered and interpreted in such a way that reliability and/or validity were compromised. Certain measures can help to

Figure 2 Survey Process

Refinement of questions from pilot company feedback

•Exploratory factor analysis •Coefficient alpha reliability

Administration to full sample to confirm factor structure

•Confirmatory factor analysis

Matching survey results to outcomes to provide criterion-related validity

•Subjective behavior ratings •Subjective injury data •Objective injury data

Generation of initial questions based on: •Review of scientific literature •Interviews with subject matter experts •Field observations •Cognitive interviews •Pilot tests

Development

Testing

Implementation

Validation

Table 1 lone Worker Survey items

Note. From “Development and Validation of Safety Climate Scales for Lone Workers Using Truck Drivers as Exemplar,” by Y.H. Huang, D. Zohar, M.M. Robertson, et al., 2013, Transportation Research Part F: Traffic Psychology and Behavior, 17, pp. 5-19; and “Development and Validation of Safety Climate Scales for Remote Workers Using Utility/ Electric Workers as Exemplar,” by Y.H. Huang, D. Zohar, M.M. Robertson, et al., 2013, Accident Analysis and Pre- vention, 59, pp. 76-86.

Level Survey item My company . . . (organization-level)

1) reacts quickly to solve the problem when told about safety concerns. 2) is strict about working safely when work falls behind schedule. 3) uses any available information to improve existing safety rules. 4) invests a lot in safety training for workers. 5) listens carefully to our ideas about improving safety. 6) tries to continually improve safety levels in each department.

My supervisor . . . (group-level)

1) discusses with us how to improve safety. 2) compliments employees who pay special attention to safety. 3) is strict about working safely even when we are tired or stressed. 4) frequently talks about safety issues throughout the work week. 5) refuses to ignore safety rules when work falls behind schedule. 6) uses explanations (not just compliance) to get us to act safely.

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maintain a survey’s scientific integrity when used in the field and strengthen employees’ engage- ment in the process.

•Invite all company employees for equal oppor- tunity to participate.

•Emphasize that participation is voluntary and confidential.

•If possible, utilize a third-party administrator to collect, store and process data.

•Analyze responses in a systematic and objec- tive process.

•Present results to all company representatives. •Engage all employees in follow-up action steps. There may be pressure to drop certain items or

add others, perhaps for fear of exposing weakness- es. This is not an option; the integrity of the scales is based on keeping them intact.

Adequate Participation The first requirement for successful application

of the safety climate survey is sufficient time and resources to engage in the process. For results to be meaningful, it is important that all employees have an opportunity to take the survey and that the response rate is adequate. For a sample to be rep- resentative, more data are ideal. Fewer responses from a group offer less representation and could also lead to a breach of anonymity. Random se- lection means that each employee has an equal chance of being selected. The more data obtained from a random sample, the more representative it will be of the entire organization.

The company should inform employees of the opportunity to participate, explain the confidential- ity of individual information and the purpose of the survey, and convey management’s commitment to improving safety. A fine line exists between en- couraging employees to participate in the survey and pressuring them to do so. Coercion may result in response bias (i.e., respondents giving answers that differ from their true feelings). Response bias can make it difficult, if not impossible, to interpret survey results. It is critical to emphasize that, al- though encouraged by the company, participation is strictly voluntary and confidential.

Management Commitment & Support The second and likely most important require-

ment is management’s commitment to act on the results. By definition, safety climate surveys focus on discrepancies between management statements and actions regarding true priorities toward safety. Management must commit to recognize, share and act positively on results.

The behavioral safety community warns against soliciting input from the employee population, then failing to act or change accordingly. In addi- tion to acting on the results, the response must be viewed as timely by the employee base. Manage- ment acting too late may be just as problematic as not responding at all. If the organization is not prepared to address possible gaps identified by the evaluation, it may not be ready to participate in a safety climate survey.

Survey Format Web-based survey technology makes it easy

to collect responses anonymously and to archive them confidentially. While computer access is not universal, access to web-enabled devices has grown. Popular electronic survey platforms pro- vide ease of use on many devices. Paper should be considered a last-resort means for safety cli- mate surveys. In such cases, OSH professionals should develop contingencies to demonstrate that respondent anonymity and response confidential- ity are preserved. An example would be to have a transcriptionist input sealed paper responses into a web-based platform, then destroy the paper ver- sion after input. Accessibility by illiterate respon- dents should also be addressed. This can involve recruiting a trusted coworker (not a supervisor) to assist in completing the survey.

Results Analysis & Interpretation OSH professionals must recognize that measur-

ing safety climate is not an end in itself but a point of departure for discussion. The act of surveying is a diagnostic process, not an intervention. The fact that strong evidence shows that safety climate is a leading indicator of safety outcomes does not mean that measuring it leads to a quick fix or au- tomatic result. Rather, measuring safety climate is a useful tool for focusing examination of safety management systems to reveal actionable insights on how to improve those systems.  Organizations should view safety climate findings as opportuni- ties to engage the entire organization in elevating safety as a daily priority, not as performance mea- sures for individuals.

The scientific rigor used to develop valid and reliable survey instruments draws on complex statistical methods, as shown in Figure 2. Com- panies using these instruments will find value in much simpler analytics and findings. Mean scores derived from aggregated safety climate survey re- sponses have significant value as comparative sta- tistics. As noted, they are used in research to assess and verify reliability and validity. The proliferation of safety climate studies has made possible catego-

Figure 3 Mean Scores of lone Worker Survey items

Note. n = 9,895 from 10 participating companies. From “Development and Validation of Safety Climate Scales for Lone Workers Using Truck Drivers as Exemplar,” by Y.H. Huang, D. Zohar, M.M. Robertson, et al., 2013, Transportation Research Part F: Traffic Psychol- ogy and Behavior, 17, pp. 5-19; and “Development and Validation of Safety Climate Scales for Remote Workers Using Utility/Electric Workers as Exemplar,” by Y.H. Huang, D. Zohar, M.M. Robertson, 2013, Accident Analysis and Prevention, 59, pp. 76-86.

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rization of safety climate mean scores. Considering measurement error, a small variance in scores may not represent a significant difference.

Additional statistical analysis is needed to test the difference. When interpreting response data, companies should assess consistency between groups as indicative that shared perception was indeed gauged. It will be valuable to explain dur- ing stakeholder discussion of survey findings that what may seem to be higher or lower mean scores between groups (e.g., 4.1 vs. 3.9) are actually not significantly different. Conversely, when statisti- cally significant differences exist between groups, discussion that explores contributing factors can be an excellent source for improvement.

An effective principle of facilitation by safety pro- fessionals is to focus on a few critical findings (e.g., significant risks to be reduced, safety management systems to be improved). Safety climate survey re- sults can be informative, particularly through ex- amination of the “% agree” statistic at the survey item level. As the term implies, this statistic reflects the percentage of respondents that indicate they agree or strongly agree with an item statement. Analysts or safety practitioners can readily iden- tify the two or three items that receive the highest and lowest percentage of agreement, and highlight them in findings reports for stakeholder discussion.

As illustrated by an example from one participat- ing company (Table 2), insight on the current state of safety as a daily priority begins to emerge. In this ex- ample, at the organization level, survey participants perceive the company’s attention to safety improve- ment and problem solving as strengths, but rate the company slightly lower when faced with pressures for on-time production. Results also indicate an op- portunity for the company to listen more to employ- ee ideas about safety. On the group level, supervisors are perceived to be strict about safety as a practice, but less so when work falls behind schedule.

Sharing & Acting on Findings As noted, leadership must be as committed to

following up with employees as it was to engaging them to participate in the survey process. Commu- nicating results and proposing how they might be

acted on is critical. This can be viewed as a spring- board for fresh ideas to produce impactful, lasting improvement and should incorporate:

•sincere thanks to respondents; •reiteration of the survey purpose; •summary of findings, including both strengths

and opportunities; •outline of what will be done to act on the op-

portunities; •encouragement for everyone to contribute to

the plan; •commitment to continuous improvement. Companies that use group-process problem

solving will recognize the value and utility of a team approach to sustainable safety climate im- provement. OSH professionals have a pivotal role as facilitators of the group process, resources for technical guidance and overseers of adjustments made to safety management systems. Everyone in the organization has a stake in the output of cross-functional teams, but, practically speaking, not all can participate in them. Operational leader- ship is the investing sponsor of the team’s efforts. These individuals should be highly visible through presence in key discussions and responsive to rec- ommendations by the teams, providing periodic progress updates for all.

Reviews of survey findings summaries, such as those illustrated in Table 2, have been put to good use by companies to initiate team discussions. Meeting facilitators find value in establishing that the team’s focus is understanding contributing factors to items with both the highest and lowest percentage of agreement, leveraging perceived strengths to act on potential opportunities. Com- panies using safety climate surveys typically find that this approach produces a flow of ideas from which adjustments can be made. A best practice in one group often can be adopted by another (see “Listening Carefully” sidebar).

Survey Frequency Safety climate has been widely and consistent-

ly shown to be a robust indicator of occupational safety, but the practical question of how frequently these surveys should be conducted must be consid-

ered. While no firm evidence exists on this question, most scientific research on the re- lationship between safety climate and incidents exam- ines events over an extended period, often 6 to 12 months (Neal & Griffin, 2006; Zohar & Luria, 2004). Best practice suggests that once per year may be appropriate.

Bergman, Payne, Taylor, et al. (2014), suggest that surveys should be collected more fre- quently to effectively predict serious injuries and propose conducting surveys as often as quarterly or monthly. The

Table 2 example Survey results Level Survey item Mean % Agree My company . . . (organization-level)

1) reacts quickly to solve the problem when told about safety concerns. 4.1 81.5 2) is strict about working safely when work falls behind schedule. 3.8 69.9 3) uses any available information to improve existing safety rules. 4.0 74.5 4) invests a lot in safety training for workers. 4.1 79.4 5) listens carefully to our ideas about improving safety. 3.8 68.6 6) tries to continually improve safety levels in each department. 4.1 81.5

My supervisor . . . (group-level)

1) discusses with us how to improve safety. 4.1 79.5 2) compliments employees who pay special attention to safety. 3.8 68.7 3) is strict about working safely even when we are tired or stressed. 4.2 83.5 4) frequently talks about safety issues throughout the work week. 4.1 82.6 5) refuses to ignore safety rules when work falls behind schedule. 3.9 70.7 6) uses explanations (not just compliance) to get us to act safely. 3.8 68.3

Management that demon-

strates unflagging

commitment to people’s well-being

can tap into the limitless potential for transforma- tion that re- sides in the

company.

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present authors, who are both researchers and consul- tants, disagree with this recommendation. The Berg- man, et al. (2014), study is based on a single company in a specialized industry and uses a unique method of data analysis that has yet to be validated. In addition, giving the same people the same survey too frequently creates some methodological concerns.

In summary, regarding the question of how fre- quently an organization should conduct safety climate surveys, based on the existing body of litera- ture, the present authors recommend an extended period, 6 to 12 months. Frequency should be de- termined based on the context, situation and need.

Conclusion When speaking on education, Robinson (2013)

said, “The real role of leadership is climate control: Creating a climate of possibility. And if you do that people will rise to it and achieve things you did not anticipate and couldn’t have expected.”

This provocative quote is as pertinent to leader- ship in safety as it is to that in education. In referring to Death Valley, Robinson describes the result of a rare 7-in. rainfall there in late 2004. The following spring, Death Valley was carpeted with wildflow- ers that germinated from seeds lying just beneath the surface of the desert floor. “Death Valley isn’t dead,” he said. “It’s dormant” (Robinson, 2013).

True commitment from the top is needed for the seeds of a strong safety climate to germinate and flourish. Management that demonstrates unflag- ging commitment to people’s well-being can tap into the limitless potential for transformation that resides in the company. Establishing safety, the continuous examination and reduction of risk, as a daily priority is a perennial challenge for orga- nizations and the individuals who comprise them. As work systems evolve toward higher complexity, the challenge is compounded. Competing urgen- cies requiring attention are increasingly diverse, as are the issues contributing to them.

Understanding these issues within an organiza- tion as predictors of incidents and injuries can open the door to implementing practical solutions. Abil- ity to highlight these issues with scientific backing increases credibility for OSH professionals and can help address concerns that might otherwise be neglected. Safety climate surveys provide this op- portunity. Intervention strategy development, in- cluding evaluation of administrative programming, implementation of procedures and restructuring of communication channels, can serve as a launching pad for lasting safety improvements. PS

references

Bergman, M.E., Payne, S.C., Taylor, A.B., et al. (2014). The shelf life of a safety climate assessment: How long until the relationship with safety-critical incidents ex- pires? Journal of Business and Psychology, 29(4), 519-540.

Christian, M.S., Bradley, J.C., Wallace, J.C., et al. (2009). Workplace safety: A meta-analysis of the roles of person and situation factors. Journal of Applied Psychol- ogy, 94(5), 1103-1127.

Federal Motor Carrier Safety Administration (FMCSA). (2016). Safety and Fitness Electronic Records System. Retrieved from http://safer.fmcsa.dot.gov

Guilford, J.P. (1954). Psychometric methods (2nd ed.). New York, NY: McGraw-Hill.

Hughes, P. & Ferrett, E. (2009). Introduction to health and safety at work. Oxford, England: Butterworth- Heinemann.

Huang, Y.H., Zohar, D., Robertson, M.M., et al. (2013a). Development and validation of safety climate scales for lone workers using truck drivers as exemplar. Transportation Research Part F: Traffic Psychology and Behavior, 17, 5-19.

Huang, Y.H., Zohar, D., Robertson, M.M., et al. (2013b). Development and validation of safety climate scales for remote workers using utility/electric workers as exemplar. Accident Analysis and Prevention, 59, 76-86.

Neal, A. & Griffin, M.A. (2006). A study of the lagged relationships among safety climate, safety motivation, safety behavior and accidents at the individual and group levels. Journal of Applied Psychology, 91, 946-953.

Psychometric Society. (2016). What is psychometrics? Retrieved from www.psychometricsociety.org/content/ what-psychometrics

Robinson, K. (2013, April). How to escape education’s Death Valley [Video file]. Retrieved from www.ted.com/ talks/ken_robinson_how_to_escape_education_s _death_valley

Zohar, D. (1980). Safety climate in industrial organi- zations: Theoretical and applied implications. Journal of Applied Psychology, 65, 96-102.

Zohar, D. & Luria, G. (2004). Climate as a social- cognitive construction of supervisory safety practices: Scripts as proxy of behavior patterns. Journal of Applied Psychology, 89, 322-333.

Zohar, D. & Luria, G. (2005). A multilevel model of safety climate: Cross-level relationships between organization and group-level climates. Journal of Applied Psychology, 90, 616-628.

listening Carefully to Our ideas about improving Safety

during a team discussion of safety climate survey findings with a cross-functional team, the facilitator was addressing organization- level item 5 (“my company listens carefully to our ideas about improving safety”). this item had one of the lowest percentage of agreement company-wide, with the exception of one remote busi- ness unit in which the element had a substantially higher mean score and one of the highest percentage of agreement recorded overall.

the team member from that operation was asked, “What is being done in your area that might be contributing to such strong agreement with that statement?”

the team member responded, “i’m betting that our monthly safety lunches have something to do with that. We come in to the shop/office and discuss incidents, near-hits and ideas on what can be done about them,” the team member said. “managers and supervisors listen and do what they can to implement them. most times, things are easy to adjust and can be done immediately, but others take a little longer. We started doing this on a quarterly basis, but it seemed to work so well we now do it once per month on a day when the most technicians can make it in. it’s very well attended. everyone gets a lot out of it and it’s a great way for us all to stay connected.”

the facilitator then said, “so, for the price of a few sandwiches or pizzas, you have this kind of discussion that undoubtedly im- proves how things are done and reminds people that they are part of the process.

the team member replied, “oh, the lunch itself is a covered dish, pot luck kind of thing. everyone brings something like it was a family get-together. it even gets a little competitive sometimes, but folks get a kick out of that, too.”

members of company leadership who were present to listen and support the team took copious notes during this exchange.