NIOSH Mining Program Report of Investigations RI 9704

Assessing the Impact of 

Safety Climate Constructs on 

Worker Performance in the 

Mining Industry

Centers for Disease Control

and Prevention

National Institute for Occupational 

Safety and Health
Report of Investigations 9704

Assessing the Impact of Safety Climate Constructs on 

Worker Performance in the Mining Industry 

Emily J. Haas, Cassandra L. Hoebbel, Patrick L. Yorio 

DEPARTMENT OF HEALTH AND HUMAN SERVICES 

Centers for Disease Control and Prevention 

National Institute for Occupational Safety and Health 

Office of Mine Safety and Health Research 

Pittsburgh, PA • Spokane, WA

April 2020 
This document is in the public domain and may be freely 

copied or reprinted.

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Suggested Citation 

NIOSH [2020]. Assessing the impact of safety climate constructs on worker 

performance in the mining industry. By Haas EJ, Hoebbel CL, Yorio PL. Pittsburgh PA: 

U.S. Department of Health and Human Services, Centers for Disease Control and 

Prevention, National Institute for Occupational Safety and Health, DHHS (NIOSH) 

Publication No. 2020-120, RI 9704. https://doi.org/10.26616/NIOSHPUB2020120

DOI: https://doi.org/10.26616/NIOSHPUB2020120

DHHS (NIOSH) Publication No. 2020-120

April 2020 

Front cover photo by NIOSH. Rear cover photo by I FOOTAGE, Shutterstock.com. 

Photos used with permission. 
Contents

Executive Summary ........................................................................................................ 1

Implications for Improving Safety Management Practices........................................ 2

Summary.................................................................................................................. 4

An Overview of Safety Climate, Culture, and their Link to Health and Safety 

Management Systems..................................................................................................... 5

Objectives ................................................................................................................ 5

Distinguishing between Climate and Culture............................................................ 6

The Relationships among Safety Climate, Health and Safety Management 

Systems, and Worker H&S Performance ................................................................. 7

Worker H&S Performance........................................................................................ 8

Safety Climate Benchmarks..................................................................................... 9

Research Objectives .............................................................................................. 10

Methodology.................................................................................................................. 11

Safety Climate Survey Development...................................................................... 11

Survey Validation ................................................................................................... 12

Recruitment and Data Collection............................................................................ 13

Survey Participants ................................................................................................ 14

Data Analysis ......................................................................................................... 16

Results .......................................................................................................................... 17

Safety Climate Benchmarks in the Mining Sector .................................................. 17

Differences among Subsectors .............................................................................. 32

Significant Predictors of Workers’ H&S Performance............................................. 32

Significant Predictors of Workers’ H&S Outcomes................................................. 36

Discussion—Improving Safety Management Practices................................................. 37

Going beyond Annual Refresher Training .............................................................. 38

Intervening to Change Risk Tolerance................................................................... 41

Improving Engagement Efforts............................................................................... 43

Maintaining Thoroughness and Improving Sense of Control.................................. 44

Accountable Communication through Performance Assessments......................... 45

Conclusion .................................................................................................................... 46

Acknowledgements ....................................................................................................... 47

References.................................................................................................................... 48

Appendix A: Safety Climate Antecedents in Worker Performance ................................ 59
Organizational Predictors of Worker Performance................................................. 59

Personal Predictors of Performance ...................................................................... 61

Appendix B: NIOSH Safety Climate Survey .................................................................. 63

Appendix C: Overall Benchmarking Results/Averages.................................................. 69

Appendix D: Overall Results/Averages for the Coal Industry (n = 358)......................... 78

Appendix E: Overall Results/Averages for Stone, Sand, and Gravel Industry

(n = 1,418)..................................................................................................................... 87

Appendix F: Overall Results/Averages for Industrial Minerals Industry (n = 907).......... 96

Appendix G: Relative Weights Results by Coal Mining Subsector.............................. 105

Appendix H: Relative Weights Results by SSG Mining Subsector.............................. 108

Appendix I: Relative Weights Results by Industrial Minerals Subsector...................... 111

Appendix J: Management Communication Scorecard for Establishing and

Maintaining Visibility.................................................................................................... 114

Appendix K: Management Communication Scorecard for Establishing and

Maintaining Consensus among the Workforce............................................................ 116

Appendix L: Management Communication Scorecard for Establishing Consistent 

Communication with the Workforce............................................................................. 118
Figures

Figure 1. Proactivity averages overall and by subsector ............................................... 18

Figure 2. Compliance averages overall and by subsector............................................. 19

Figure 3. Organizational support for health and safety averages overall and

by subsector.................................................................................................................. 20

Figure 4. Supervisor support for health and safety averages overall and

by subsector.................................................................................................................. 21

Figure 5. Supervisor communication about H&S averages overall and by subsector ... 22

Figure 6. Coworker communication about H&S averages overall and by subsector..... 23

Figure 7. Worker engagement averages overall and by commodity overall and

by subsector.................................................................................................................. 24

Figure 8. Health and safety training adequacy averages overall and by subsector....... 25

Figure 9. Worker adaptability averages overall and by subsector................................. 26

Figure 10. Worker risk tolerance averages overall and by subsector............................ 27

Figure 11. Worker sense of control averages overall and by subsector........................ 28

Figure 12. Worker thoroughness averages overall and by subsector............................ 29

Figure 13. Health and safety knowledge averages overall and by subsector................ 30

Figure 14. Health and safety motivation averages overall and by subsector................. 31

Figure 15. Excerpt from CRH Oldcastle Materials Group ART...................................... 40

Figure 16. NIOSH safety climate survey cover sheet.................................................... 64

Figure 17. Page 1 of the NIOSH safety climate survey with questions assessing 

perceived proactivity, compliance, sense of control, thoroughness, and

risk tolerance................................................................................................................. 65

Figure 18. Page 2 of the NIOSH safety climate survey with questions assessing 

perceived organizational support for H&S, coworker communication, supervisor

support for H&S, supervisor communication, and worker engagement......................... 66

Figure 19. Page 3 of the NIOSH safety climate survey with questions assessing 

perceived H&S knowledge, H&S motivation, H&S training adequacy, worker 

adaptability, and frequency of near misses and incidents experienced in the

last 6 months................................................................................................................. 67

Figure 20. Demographic page of the NIOSH safety climate survey .............................. 68
Tables

Table 1. Characteristics of safety climate and safety culture........................................... 6

Table 2. Organizational factors that predict performance.............................................. 12

Table 3. Person-related factors that predict performance ............................................. 12

Table 4. Breakdown of participation by mined subsector.............................................. 14

Table 5. Demographic characteristics of participants.................................................... 14

Table 6. Experience in current job (69 missing) ............................................................ 15

Table 7. Experience at current mine (155 missing) ....................................................... 15

Table 8. Experience in the mining industry (106 missing) ............................................. 15

Table 9. Weighted impact of safety climate constructs on worker proactivity

using overall sample. All 10 constructs are significant at the p = .05 level .................... 33

Table 10. Weighted impact of safety climate constructs on worker compliance

using overall sample. All 10 constructs are significant at the p = .05 level .................... 34

Table 11. Weighted impact of safety climate constructs on worker H&S knowledge.

All 10 constructs are significant at the p = .05 level....................................................... 35

Table 12. Weighted impact of safety climate constructs on worker motivation.

All 10 constructs are significant at the p = .05 level....................................................... 35

Table 13. Impact of safety climate constructs on worker H&S outcomes ...................... 36

Table 14. Results for proactivity items overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 70

Table 15. Results for compliance items overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 70

Table 16. Sense of control overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 71

Table 17. Thoroughness overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 71

Table 18. Risk tolerance overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 72

Table 19. Organizational support for H&S overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 72

Table 20. Coworker communication overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 73

Table 21. Supervisor support overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 73

Table 22. Supervisor communication overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 74
Table 23. Worker engagement overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 75

Table 24. H&S knowledge overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 75

Table 25. H&S motivation overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 76

Table 26. H&S training adequacy overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 76

Table 27. Adaptability overall for each response option (%)

and item average (on a 6-point scale)........................................................................... 77

Table 28. Proactivity in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 79

Table 29. Compliance in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 79

Table 30. Sense of control in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 80

Table 31. Thoroughness in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 80

Table 32. Risk tolerance in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 81

Table 33. Organizational support for H&S in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 81

Table 34. Coworker communication in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 82

Table 35. Supervisor support in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 82

Table 36. Supervisor communication in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 83

Table 37. Worker engagement in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 84

Table 38. H&S knowledge in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 84

Table 39. H&S motivation in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 85

Table 40. H&S training adequacy in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 85

Table 41. Adaptability in coal for each response option (%)

and item average (on a 6-point scale)........................................................................... 86
Table 42. Proactivity in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 88

Table 43. Compliance in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 88

Table 44. Sense of control in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 89

Table 45. Thoroughness in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 89

Table 46. Risk tolerance in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 90

Table 47. Organizational support for H&S in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 90

Table 48. Coworker communication in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 91

Table 49. Supervisor support for H&S in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 91

Table 50. Supervisor communication in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 92

Table 51. Worker engagement in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 93

Table 52. H&S knowledge in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 93

Table 53. H&S motivation in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 94

Table 54. H&S training adequacy in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 94

Table 55. Adaptability in SSG for each response option (%)

and item average (on a 6-point scale)........................................................................... 95

Table 56. Proactivity in industrial minerals for each response option (%)

and item average (on a 6-point scale)........................................................................... 97

Table 57. Compliance in industrial minerals for each response option (%)

and item average (on a 6-point scale)........................................................................... 97

Table 58. Sense of control in industrial minerals for each response option (%)

and item average (on a 6-point scale)........................................................................... 98

Table 59. Thoroughness in industrial minerals for each response option (%)

and item average (on a 6-point scale)........................................................................... 98

Table 60. Risk tolerance in industrial minerals for each response option (%)

and item average (on a 6-point scale)........................................................................... 99
Table 61. Organizational support for H&S in industrial minerals for each

response (%) and item average (on a 6-point scale)..................................................... 99

Table 62. Coworker communication in industrial minerals for each response (%)

and item average (on a 6-point scale)......................................................................... 100

Table 63. Supervisor support for H&S in industrial minerals for each response (%)

and item average (on a 6-point scale)......................................................................... 100

Table 64. Supervisor communication in industrial minerals for each response (%)

and item average (on a 6-point scale)......................................................................... 101

Table 65. Worker engagement in industrial minerals for each response (%)

and item average (on a 6-point scale)......................................................................... 102

Table 66. H&S knowledge in industrial minerals for each response (%)

and item average (on a 6-point scale)......................................................................... 102

Table 67. H&S motivation in industrial minerals for each response (%)

and item average (on a 6-point scale)......................................................................... 103

Table 68. H&S training adequacy in industrial minerals for each response (%)

and item average (on a 6-point scale)......................................................................... 103

Table 69. Adaptability in industrial minerals for each response option (%)

and item average (on a 6-point scale)......................................................................... 104

Table 70. Impact of safety climate constructs on worker performance (proactivity

and compliance), knowledge, and motivation in the coal mining industry ................... 106

Table 71. Impact of safety climate constructs on H&S outcomes in the

coal mining industry..................................................................................................... 107

Table 72. Impact of safety climate constructs on worker performance (proactivity

and compliance), knowledge, and motivation in the stone, sand, and gravel industry 109

Table 73. Impact of safety climate constructs on H&S outcomes in the stone,

sand, and gravel industry ............................................................................................ 110

Table 74. Impact of safety climate constructs on worker performance (proactivity

and compliance), knowledge, and motivation in the industrial minerals industry......... 112

Table 75. Impact of safety climate constructs on H&S outcomes in the industrial 

minerals industry ......................................................................................................... 113
Acronyms and Abbreviations 

ART annual refresher training

CPWR Center for Construction Research and Training

H&S health and safety

HSMS health and safety management system

ICMM International Council on Mining and Metals

MSHA Mine Safety and Health Administration

NAS National Academy of Sciences

NMA National Mining Association 

NIOSH National Institute for Occupational Safety and Health

NRC National Research Council

OSHA Occupational Safety and Health Administration

PPE personal protective equipment

RS-RW rescaled relative weights

RWA relative weights analysis

SPSS Statistical Package for the Social Sciences
1

Executive Summary

To advance a more tangible understanding of health and safety climate in the U.S. mining 

industry, the National Institute for Occupational Safety and Health (NIOSH) surveyed members 

of mining workforces about experiences at their respective mine operations. The survey 

measured four personal (i.e., risk tolerance, thoroughness, sense of control, and adaptability) and 

six organizational (i.e., organizational support, supervisor support, supervisor communication, 

coworker communication, worker engagement, and training) constructs to determine significant 

influences on health and safety (H&S) performance, which was measured in the form of worker 

proactivity, compliance, and reported near misses or other incidents. This report, unlike other 

safety climate reports, focuses on individual perceived safety climate [Neal and Griffin 2006] 

versus crew-based approaches to such assessments.

Participants consisted of 2,683 workers—both salaried and hourly—at 39 mine sites throughout 

17 states. The mines represented nine major companies and three mining subsectors (coal, stone, 

sand, and gravel, and industrial minerals). This report analyzes, assesses, and presents data about 

these safety climate constructs to help those who manage companies, mine organizations, or 

groups of workers, to develop, target and improve, or implement parts of a health and safety 

management system (HSMS) to support workers’ H&S performance while reducing the 

likelihood of workplace incidents.

The results within this report establish initial benchmarking data for each construct measured. 

The overall benchmarking data, or averages, along with the benchmarks for each subsector, are 

visually shown in Figures 1 to 14. A score of six represents the highest perception of the 

construct being measured. In general, most averages were between 4.5 and 5.5, indicating 

generally positive perceptions. Regarding the regression analyses, some highlights include the 

following:

• All 10 safety climate constructs were statistically significant predictors of proactivity; the 

overall model fit was R2 = .32, or 32.24%. Thoroughness and sense of control were the 

highest predictors at 21% and 17% of the total variance, respectively. Workers’ personal 

levels of risk tolerance (13%) and their engagement in H&S activities (12%) were also 

strong predictors.

• All 10 safety climate constructs were statistically significant predictors of compliance; 

the overall model fit was R2 = .46, or 46.70%. Workers’ risk tolerance was the 

predominant predictor at almost 31% of the total variance of R2. Workers’ thoroughness 

(23%) and then coworker communication (11%) were strong predictors of workers’ 

compliant behaviors. H&S training, although a significant predictor, only contributed 

about 5% to the total variance of the 46.7% model. Organizational support for H&S 

contributed about 4%.

• The overall fit for the knowledge model was R2 = .5, or 50.03%. The fit for the 

motivation model was R2 = .39, or 39.74%. Although training significantly and heavily 

contributed to workers’ knowledge and motivation, the proactivity and compliance 

models show that it does not necessarily translate to H&S performance.
2

• The final models included the four incident-related variables measured in the survey. 

Together, the 10 safety climate constructs predicted approximately 8% (R2 = 8.26%) of 

near misses experienced; 6% (R2 = 5.72%) of first aid incidents experienced; 7% (R2 = 

7.29%) of incidents experienced that required medical treatment; and 6% (R2 = 6.13%) of 

days lost among participants.

Implications for Improving Safety Management Practices 

The results provide insights into how to support workers’ H&S on the job as well as support

what previous reports have found. Notably, the results showed that the personal constructs were 

the most influential safety climate constructs in predicting workers’ H&S performance. These 

results also show the value of organizations accounting for and addressing both the 

organizational and personal factors where possible. In response, interventions can be employed 

on an organizational level among varying types of management to influence workers’ personalbased factors on the job.

Broadly, NIOSH researchers identified five areas of focus that emerged from the results. These 

areas can be used to develop or enhance various workplace HSMS interventions. These areas, 

detailed below, are presented in no particular order, as each organization likely has a different 

culture with strengths and weaknesses. It is anticipated, however, that at least one of these areas 

is ripe for intervention with an organization.

1. Go Beyond Annual Refresher Training

Although training emerged as a strong predictor of workers’ knowledge on the job, it had a 

smaller effect on workers’ actual H&S performance in terms of proactivity and subsequent 

decision making. Future research will need to determine if these results are a result of the 

training itself, or the support from management subsequent to the training. Assuming that most 

training is adequate, considering the high benchmark as well as its significant contribution to 

worker knowledge within the study, management may need to focus on improving workers’ 

opportunities and involvement regarding their roles in work processes and practices to increase 

workers’ sense of control, as well as actual control, and confidence. Research has shown that the 

transfer of any knowledge gained through training will not occur if workers do not have adequate 

levels of self-efficacy and control as well as support from their management [Grossman and 

Salas 2011]. Therefore, rather than work to “provide more training,” improving the content of 

training as well as the level of follow-up and communication that takes place when the training is 

over should be considered. Examples of how some companies have tried to address soft skills 

during trainings and subsequently on the job are discussed in this report.

2. Acknowledge and Address Risk Tolerance and Associated Decisions

Risk tolerance emerged as a steady, significant predictor of worker H&S performance—

particularly among workers’ compliant decisions to follow rules. Risk tolerance is an emergent 

state that can be changed over time and it could behoove management to address this factor. In 

general, most operations have mechanisms in place for hazard identification and subsequent risk 

perception such as job safety analyses, as reported by the Occupational Safety and Health 

Administration (OSHA) [OSHA 2002]. However, the greatest threat is usually not missing a 

hazard but rather, failing to mitigate the hazard due to a high tolerance for risks [Fennell 2015; 

Jones 2015]. These researchers argued that, rather than build knowledge around hazard 
3

recognition and risk perception, more attention should be given to enhancing not only knowledge 

and skills but also autonomy around third step—the decision-making process. Fennell [2017, 

2015] has proposed 10 factors that are similar to findings from previous research [e.g., Eklöf and 

Törner 2002; Harrell 1990; Huang et al. 2007; Mearns et al. 2001b; Rundmo 2001] that influence 

risk tolerance. These factors can be and have been observed at several mine sites, where they 

were seen to prompt specific conversations around this issue.

3. Enhance Worker Engagement Opportunities

Engagement, although measured as an organizational construct in the NIOSH survey, has both 

organizational and individual origins, which may be one of the reasons it was a significant, 

moderately sized predictor within all of the models. Although engagement as a construct in the 

current research effort scored as one of the lowest perceived organizational factors, it is 

important to note that engagement is made up of quickly changing moments and occurs in more 

of an ebb and flow [Kahn 1990]. Examples that participants and organizational management

discussed as employee-involvement initiatives that seemed to “work” on site in terms of being 

recognized by workers include:

• Letting workers choose a new type of personal protective equipment (PPE) based on a 

variety of approved options.

• Creating and involving workers on different health and safety committees, including 

participation in walk-throughs and debriefs on site. Additionally, targeting groups who 

appear to have lower perceptions of the degree of risk or morale has shown success.

• Improving communication quantity and quality throughout the workday.

4. Maintain Worker Thoroughness and Improve Sense of Control

While making some of the aforementioned changes to the organization’s HSMS, it is important 

to keep in mind that the safety climate results showed that workers’ personal factors have a 

larger impact on their H&S performance. Although these are personal factors, these individual 

states can be influenced by organizational characteristics such as decision-making authority

bestowed onto an individual, opportunities provided to use knowledge and skills, and the option 

and ability to participate [Karasek and Theorell 1990]. It can be suggested, then, that the root 

cause, and perhaps a potential solution, of organizational conflicts regarding workplace safety 

may reside in understanding the processes undertaken by organizations to communicate with 

individuals. For example, determining if a safety initiative is not endorsed as it should be can be 

useful in determining misaligned communications. Through increased engagement and 

collaboration efforts, it may be easier to facilitate alignment between management and hourly 

workers.

5. Be Accountable for Communication Practices

Because safety communication has been continuously encouraged in high-risk industries as an 

effective mechanism to enhance workers’ awareness of safety and appropriate response to risks 

[Clarke 2003; Griffin and Neal 2000; Mearns et al. 2003; Probst 2004], results from NIOSH’s 

safety climate survey can be used to improve communication quantity and quality. NIOSH 

research has been able to show gaps and best practices [Haas 2019; Haas et al. 2018b; Haas et al. 

2016; Haas and Yorio 2016] and that there is room for improvement. Building on this research, 

NIOSH used the current results and additional data points to develop communication 
4

accountability scorecards to improve the transparency of organizational communication. Using 

such tools (Appendices J, K, L) can help make communication more tangible.

Summary

Besides establishing current benchmarks of safety climate in the mining industry, these results 

show the impact that organizational and personal safety climate factors can have on workers’ 

H&S performance. Specifically, this report provides some guidance to mines for improving 

organizational factors to help enhance the overall culture, regardless of the starting perspectives 

or points of view of individual miners. It is believed that organizations can start to address a 

select number of HSMS practices and, over time, scale their systems to include additional 

indicators.
5

An Overview of Safety Climate, Culture, and their Link to Health and 

Safety Management Systems

Although the term “safety climate” was not coined until 1980 when Zohar discussed workers’ 

attitudes towards safety, such measurements were occurring much earlier [Healey et al. 2012; 

Zohar 1980]. Specifically, organizational behavior literature has been concerned with 

organizational climate since the 1960s [see Frederikson 1966; Friedlander and Margulies 1969; 

Schneider and Barbera 2014; Tagiuri and Litwin 1968]. Scholars discuss organizational climate 

as any perception that emerges as a result of individual’s activities and interactions within their 

organization [Schneider and Hall 1972]. In occupational health and safety (H&S), it is common

to focus on safety when referring to an organization’s climate—hence the arrival of the heavily

used term safety climate. An organization’s safety climate refers to employees’ perceptions of 

their organization’s values and priority of H&S on the job [Griffin and Curcuruto 2016]. The 

interaction between individual and organizational factors plays a critical role in maintaining a 

satisfactory safety climate and, in turn, safe work practices and operations [Christian et al. 2009; 

Hofmann et al. 2003; Reason 2016].

Although safety climate is often studied and referenced as a leading indicator of incidents [Haas 

and Yorio 2016; Juglaret et al. 2011; Mearns et al. 2001a; Payne et al. 2009; Schneider 2017], 

identifying and implementing tangible methods to improve an organization’s safety climate is 

not well understood, particularly in organizations whose environments are in a state of constant 

change. Research continues to suggest that safety climate models can support root cause analyses 

and trends, particularly to identify vulnerable areas within a company’s health and safety 

management system [Griffin and Curcuruto 2016; Reason 2008]. Specific to mining, the 

National Research Council’s (NRC) National Academy of Sciences (NAS) [NRC 2013] 

indicated that a positive safety culture is a critical aspect of preparation that needs to be 

considered within any HSMS. To that end, this report focuses on (1) the assessment of workers’ 

perceptions of safety climate; (2) which safety climate constructs have a greater impact on 

worker H&S performance (performance is comprised of proactive and compliant behaviors on 

the job); and (3) how organizations can effectively use HSMS interventions to improve select

safety climate constructs that are significant predictors of workers’ H&S performance.

Objectives

To advance a more tangible understanding of safety climate, the National Institute for 

Occupational Safety and Health (NIOSH) surveyed members of mining workforces about 

experiences at their respective mine operations. The survey measured personal and 

organizational constructs, or factors, to determine significant influences on H&S performance. 

This report conveys information about these safety climate constructs to help those who manage 

mine companies, a mine organization, or groups of workers, to develop, improve, and implement

parts of an HSMS to support worker H&S performance while reducing the likelihood of 

workplace incidents. To that end, this report includes the following:

• A review of safety climate, culture, and health and safety management systems.

• Safety climate constructs measured to predict worker proactivity and compliance.
6

• Key findings about workers’ perceptions of safety climate constructs, including 

differences among the mining subsectors that were surveyed as well as a benchmark of 

perceived norms for each construct measured.

• Key findings about safety climate constructs that significantly predict workers’ proactive 

and compliant behaviors on the job.

• Considerations for organizational leadership to help improve and maintain critical safety 

climate constructs to support the organization’s execution of its HSMS. 

Distinguishing between Climate and Culture

The current report specifically addresses constructs of safety climate. Specifically, this report, 

unlike other safety climate reports, focuses on individual perceived safety climate versus crewbased approaches to such assessments [Christian et al. 2009; Neal and Griffin 2006]. However,

safety climate and safety culture, despite having distinctions that make them unique, are often 

used interchangeably, both in the literature and in practice [Cox and Flin 1998]. Some of their 

unique characteristics, including definitions and measurement issues, are highlighted in Table 1.

Table 1. Characteristics of safety climate and safety culture

Characteristics Safety climate Safety culture

Paraphrased

definitions

• Perceived priority of values and 

assumptions at a given point in time with 

regard to policies, practices, and 

processes [Guldenmund 2010; Zohar 

2010]

• “A summary of molar perceptions that 

employees share about their work 

environments” [Zohar 1980, p. 96] 

• A snapshot of the current state of safety 

[Lee 1981] or what happens on a day-today basis [Gillen et al. 2014]

• Implicit safety values and assumptions that 

guide workers’ practices [Griffin and 

Curcuruto 2016]

• “Shared and learned meanings, experiences, 

and interpretations of work and safety” that

are fostered within an organization over time 

[Richter and Koch 2004, p. 704]

• A set of dominant indicators, beliefs, and 

values with regard to job safety [Fang et al. 

2006] that eventually manifest in safetyrelated actions [Gillen et al. 2014]

Measurement 

issues

• Tend to capture a poor-to-positive 

perception of safety features (e.g., where 

lower scores represent a poor safety 

climate and higher scores represent a 

positive safety climate) [Neal et al. 

2000]

• Harder to study, measure, and assess [Schein

1990] and researchers are skeptical about only 

quantitative measurements of safety culture 

[Guldemund 2007]

Other conceptual 

issues

• Neal et al. [2000] conceptualized a 

higher order of organizational safety 

climate that includes four dimensions of 

climate: 1. management values; 2. safety 

communication; 3. safety training; and 4. 

safety systems

• Schein [1999] conceptualized three embedded 

levels of culture: 1. organizational artefacts; 

2. organizational norms and values that 

contribute to how artefacts are modelled; and 

3. basic assumptions that members hold about 

their organization’s reality and functioning
7

Importantly, an agreed-upon characteristic that distinguishes these two concepts is that safety 

climate assessments provide an understanding of the current safety conditions and values to

provide guidance into factors that can be positively altered [Curcuruto and Griffin 2018; 

Curcuruto et al. 2016]. In other words, aspects of safety climate can be more readily measured 

and alerted to improve H&S performance. Therefore, this study focused on safety climate in the 

mining sector to provide targeted insights into what aspects of an organization’s climate can be 

developed or more effectively implemented through the HSMS to improve organizational and

worker H&S performance.

The Relationships among Safety Climate, Health and Safety Management Systems, 

and Worker H&S Performance

Health and safety management systems are commonly referred to as a set of institutionalized, 

interrelated, and interacting practices used to establish and achieve occupational H&S goals 

(ANSI/AIHA Z-10; OHSAS 18001). Even if definitions vary, actions implemented by 

organizations usually entail steps around the Plan-Do-Check-Act cycle [PCDA; aka, “the 

Shewhart cycle,”] [Deming 1986]. Research has argued for a focus on specific elements within 

an HSMS. Specifically, it has been argued that an explicit and implicit goal of an HSMS should 

be to develop a strong safety climate [Health and Safety Executive 1991]. Additionally, 

organizations are encouraged and, to some degree, expected to employ a risk-based framework 

for hazard identification and mitigation [Frick et al. 2000; Grayson et al. 2006; International 

Council on Mining and Metals (ICMM) 2015]. Such risk-based processes also include the 

application of controls to minimize negative outcomes as well as verifying that controls remain 

effective over time.

Despite a common understanding of the importance of having an HSMS, integrating the use of 

formal tools, interventions, and practices has been challenging. Difficulties in committing to the 

development and evaluation of HSMS interventions, specifically, have created a lack of 

understanding about the implementation of these systems and its ties to safety climate in a given 

organization [ICMM 2015; Robson et al. 2007]. However, an examination of the common 

elements and practices of company health, safety, and risk management systems as well as 

common constructs of safety climate show overlap in key dimensions such as leadership, 

communication, risk assessment, and worker involvement [Bushnell 1992; Deming 1986; Haas 

et al. 2018a]. Therefore, it is plausible to believe that measurements of safety climate can be 

better integrated into a continuous HSMS cycle and, as a result, effectively alter and improve 

work practices and H&S performance on site.

Research has argued that if there are too few dimensions of safety climate measurement and 

focus, interventions might not align with the most important aspects of an organization’s HSMS

and, consequently, be less effective [Zohar 2010]. Therefore, a positive safety climate and 

complementary HSMS are more likely to occur if workers are motivated and feel supported in 

complying with organizational procedures and processes. Thus, understanding how to best assess 

and improve safety climate is critical to the effective implementation of HSMSs and subsequent 

incident prevention. 

Meta-analyses have identified connections between organizational aspects of safety climate and 

workers’ proactive H&S performance [see Brondino et al. 2012; Bronkhorst 2015; Dahl and 

Kongsvik 2018; Flin et al. 2000; Nahrgang et al. 2011; Neal and Griffin 2006]. Therefore, it is 
8

not surprising that safety climate has also been linked to safety outcomes [Clarke and Ward, 

2006; DeJoy 2005; Neal and Griffin 2006]. Although research has shown that worker proactivity

and compliance can predict job performance [Grant et al. 2009; Thompson 2005; Crant 1995],

the constructs that most influence these actions are not clear, emphasizing the value of further

inquiry [Parker et al. 2006]. On an organizational level, empirical evidence is needed to 

understand how and in what ways the organization’s safety climate intersects with workers’

perceptions and performance within the overall HSMS.

Worker H&S Performance 

Previous research [Griffin and Neal 2000; Christian et al. 2009; Neal and Griffin 2006] has 

positioned organizational- and personal-related factors as antecedents, or predictors, of worker 

safety knowledge and motivation, which, in turn, predicts worker behaviors, which then predicts 

incidents. Reason et al. [1998] suggest that, rather than focus on injuries that contribute to days 

lost which are (fortunately) rare occurrences, broader measures around knowledge, motivation, 

and behavior are able to provide organizations with continuous feedback. Specifically, the 

personal safety perceptions of workers and the less severe incidents that they experience are 

always present and give a current snapshot of H&S in the organization [Zacharatos et al. 2005]. 

Consequently, in the current NIOSH study, the dependent variables measured were worker

knowledge, motivation, and behavior. Behavior was studied through measures of H&S 

performance in the form of proactivity and compliance. The determinants of H&S performance 

have been shown to represent factors directly responsible for compliance and proactivity 

[Campbell et al. 1993; Neal et al. 2000]. These dependent variables are highlighted below.

Worker Proactivity: Survey items 1–5

Proactivity (discussed as participation in some studies) is an extra-role behavior. Actions include 

anticipating future events, taking initiative to improve current conditions, not passively adapting 

to present conditions, being self-starting and taking charge, speaking out with ideas, and 

overcoming safety barriers [Clarke and Ward 2006; Crant 2000; Frese et al. 1996; Hofmann et 

al. 2017; Griffin and Neal 2000; Parker et al. 2010]. Worker proactivity has also been shown to

predict workers’ actions which stems, in part, from workers’ increased likelihood to engage in

situational awareness and voice concerns about safety [Grant et al. 2009; Thompson 2005; 

Tucker and Turner 2015]. Despite research documenting common features of proactivity, little is 

known about what organizational and personal factors influence these extra-role behaviors taken 

on by workers [Parker et al. 2006]. A proactivity scale was adapted from Neal et al. [2000] to 

measure workers’ proactive safety actions. These are items 1–5 in the survey.

Worker Compliance: Survey items 6–9

Safety compliance is defined by Griffin and Neal [2000] as “the core safety activities that need to 

be carried out by individuals to maintain workplace safety” [p. 349]. These researchers contend 

that safety compliance is a function of knowledge, skills, and motivation to comply with safety 

policies and processes. In other words, compliance involves inner-task role behaviors such as 

wearing proper personal protective equipment and following workplace rules [Clarke and Ward 

2006]. A safety compliance scale was adapted from Neal et al. [2000] and Zacharatos et al. 

[2005] to measure workers’ compliance with safety procedures. These are items 6–9 in the 

survey.
9

Worker Knowledge and Motivation: Survey items 43–45 and 46–48

An organization’s safety climate has been shown to influence worker knowledge, motivation, 

and skills through increased participation and adherence to H&S activities [Morrison et al. 1997; 

Neal et al. 2000; Zacharatos et al. 2005]. Specifically, worker knowledge and motivation have 

been shown as determinants of differences in individual worker performance [Campbell et al. 

1993]. The current survey adapted items from previous studies [Neal et al. 2000; Zacharatos et 

al. 2005] to assess worker knowledge and motivation. These are items 43–45 and 46–48 in the 

survey.

Near Misses and other Incidents: Survey items 55–58

Workers who participated in the survey were asked to report their frequency of near misses and 

other incident occurrences on site in the last six months. According to the National Safety 

Council [NSC 2013], a near miss is an “unplanned event that did not result in injury, illness, or 

damage—but had the potential to do so” (np). Regarding accuracy, six months is the 

recommended maximum time over which workers should be asked to recall injuries [Veazie et 

al. 1994; Zacharatos et al. 2005]. To that end, each participant was asked how often they were 

involved in the following in the last six months: a near miss incident; incident that required first 

aid; incident that required medical treatment; incident that resulted in days lost on the job. Each 

participant was prompted to check one of the following: Never, Once, 2 times, 3 times, 4 times, 

or 5+ times. These are items 55–58 in the survey.

Although there is regulatory oversight within the U.S. mining industry to require near miss 

reporting, it is well known that underreporting occurs in the industry [Nowrouzi-Kia et al. 2017]. 

However, many mine sites, including those who participated in the study, do have informal and 

formal near miss reporting procedures and forms that encourage workers to complete any near 

miss observed, prevented, or fixed on site. For most of the sample, the four types of incidents 

could be cross-checked with the participating mine sites due to their own reporting and auditing 

of incidents. At those sites who engaged in cross-checking, the results were often very close, 

indicating an understanding and accurate recollection of near misses or incidents experienced in 

the last six months. Obviously, this cross-checking was not possible with all participating mines 

and it can be assumed that underreporting still existed in some areas. However, an analysis of the 

near miss data in the middle of data collection showed that, although about half of the sample 

indicated experiencing no incidents, the model was not subject to a zero-inflated model with the 

mean of near misses being .83 [Haas and Yorio 2019]. Rather, zero-inflated models should be 

considered when the mean is <.07 or <.05 [Lord et al. 2005]. Therefore, researchers were 

comfortable with the incident reporting provided by participants.

Safety Climate Benchmarks

For the mining sector to assess and improve safety climate at the organizational level, it is 

necessary to establish benchmarks to enable future measurement. A recent review of H&S 

literature in the past 100 years found that, both within the literature and among practitioners, no 

consistent measure of safety climate exists [Hofmann et al. 2017]. Additionally, an NAS report 

by the NRC [2013] advocated that more data encompassing the general mining industry was 

needed to make more generalizable conclusions as well as establish benchmarks within the 
10

industry. Thus, the establishment of benchmarks for future mining assessments was one goal of 

this investigation.

Benchmarking is defined as “a process of continuously measuring and comparing an 

organization’s business processes against those of process leaders anywhere in the world to gain 

information which will help the organization to take action to improve its performance” 

[American Productivity & Quality Centre 1993, p. 1]. Another definition describes 

benchmarking as, “A method of measuring and improving organizational performance by 

comparing with the best” [Stapenhurst 2009, p. 6]. In other words, benchmarking allows 

organizations to identify areas where they are doing well as well as areas that need improvement 

[Healey et al. 2012].

Researchers [Ahmed and Rafiq 1998; Stapenhurst 2009] suggested practical aspects of 

benchmarking such as being able to employ systematic procedures to allow for the comparison 

of performance levels among organizations and groups. Another example provided was being 

able to emphasize continuous improvement through the identification and adoption of practices 

that can lead to greater levels of performance. Benchmarking safety climate in the mining 

industry allows organizations to quantify performance levels and identify gaps in which 

organizational constructs could be improved upon to support improved proactive and compliant 

performance.

The current safety climate data serve as benchmarks for mine organizations to gauge their 

performance in advancing worker H&S through a stronger, more integrated health, safety, and 

risk management strategy. Even more importantly, prioritizing the impact of climate constructs 

gives practitioners a road map of where to focus intervention efforts, based on which constructs 

need attention. Therefore, the current analysis process, like others in high-risk occupations [e.g., 

Mearns et al. 2001b], identifies areas in which mine organizations can improve. However, the 

organization’s actual improvement ultimately depends on how each respective organization

chooses to use the results to make changes.

Research Objectives

This study sought to accomplish the following research objectives:

• Determine a benchmark of each safety climate construct measured to enable other 

organizations to quantify and compare their current safety climate within the context of 

NIOSH’s sample.

• Among the personal and organizational safety climate constructs measured, determine 

which are the most influential in predicting proactive performance among workers.

• Among the personal and organizational safety climate constructs measured, determine 

which are the most influential in predicting compliant performance among workers.

• Determine implementation efforts to inform communication and assessment at varying 

levels within mine organizations.
11

Methodology

NIOSH assembled a safety climate survey specific to the mining sector that was used to assess 

workers’ perceptions of several personal and organizational constructs.

Safety Climate Survey Development

A literature review was conducted focusing on a variety of terms and concepts related to safety 

climate and culture measurement in high-risk occupations. Specifically, literature on safety 

climate, safety culture, HSMSs, and organizational values rendered common measures or 

predictors used to assess safety climate. Common measures applicable to the mining industry 

were selected including those that were organizational and personal predictors of workers’ H&S 

performance (hereafter known as worker proactivity and worker compliance). Specifically, 

prominent causal and theoretical models of workplace safety were consulted to identify relevant 

constructs [e.g. Christian et al. 2009; Neal and Griffin 2000; Griffin and Neal 2000; Mearns et al. 

2001a, b; Zacharatos et al. 2005]. NIOSH utilized several key constructs from the model 

depicted in the Christian et al. [2009] meta-analysis. A unique contribution argued by these

researchers is the promotion of both organizational- and person-related factors as predictors.

NIOSH identified six organizational constructs and four personal constructs deemed necessary to

foster a positive safety climate that could also influence H&S behaviors. NIOSH researchers

were also able to locate existing validated scales through the cross-industry occupational H&S 

peer-reviewed literature that were ripe for adaptation to the mining industry. This approach is 

common when developing quantitative instruments [DeVellis 2012]. Adapted questions within 

each scale were tested with a subject matter expert in the mining industry prior to pilot testing in 

the field. Tables 2 and 3 list each construct, a brief definition, and original sources for scale 

adaptation. Each construct is detailed in Appendix A. The survey is shown in Appendix B.
12

Table 2. Organizational factors that predict performance

Scale Construct Definition Previous Validation

Supervisor H&S 

Support

Supervisors’ valuing employees’ contributions to the 

organization, caring about their personal well-being, 

and emphasizing safe choices

Eisenberger et al. 2002

Supervisor H&S 

Communication

Supervisors’ sharing of safety information and the 

ease with which workers can communicate with their 

supervisors about H&S issues

Casey and Krauss 2013

Organizational 

H&S Support

The organization’s priority for safety, including 

expectations about the balance of work pace, 

workload, and production pressure 

Katz-Navon et al. 2005

Adequate H&S 

Training

The quantity and quality of training in increasing 

knowledge, awareness of hazards, and behaviors 

needed to avoid injury 

Zacharatos et al. 2005

Worker 

Engagement

Willingness of the organization to involve employees 

in decision-making processes about procedures that 

influence their tasks

Niehoff and Moorman

1993; Zacharatos et al. 

2005

Coworker 

Communication

Coworkers’ talking about H&S, holding each other 

accountable for safe work practices, and accepting

mistakes as learning experiences

Zacharatos et al. 2005

Table 3. Person-related factors that predict performance

Scale Construct Definition Previous Validation

Adaptability Active-change orientation to bring about constructive 

change, similar to “felt responsibility for change” 

Parker et al. 2006

Sense of 

Control/Efficacy

Subjective well-being, job satisfaction, and sense of 

control over their outcomes

Judge et al, 2003; Gardner 

and Pierce 2010 

Risk Avoidance General tendency to take risks or avoid risks on the 

job

Meertens and Lion 2008

Thoroughness The degree to which individuals believe they are 

orderly, dependable, and responsible

Barrick and Mount 1991; 

Poropat 2009

These factors have been used in previous studies to predict proactivity, compliance, or incidents.

The survey used a 6-point Likert scale, with responses ranging from Strongly Disagree to 

Strongly Agree. Each item relates to one of a series of constructs, and responses were used to 

calculate a mean score for each construct. A score of 6 represents a high perception of the safety 

climate construct while a score closer to 1 represents a poor perception of the construct.

Survey Validation

After the NIOSH Institutional Review Board approved the survey and research design, the 

survey was piloted in 2015 during several field visits. These pilot-tested data were not part of the 
13

final survey sample. In this initial pilot, the Cronbach alpha’s ranged from .6 to .9, which are 

acceptable values [Bland and Altman 1997; Devellis 2012; Nunnally and Bernstein, 1994]. In 

addition, reliability checks were completed at two other time points throughout data collection at 

which the alpha levels remained steady.

After initial pilot testing, the age and experience categories were slightly edited in response to 

mine corporate-level feedback. Particularly, with baby boomers getting ready to retire, industry 

representatives felt that over 16 years in the experience categories would render too large a 

sample; they recommended the survey have a 16–20-year option and then an option with more 

than 20 years of experience. Similarly, they felt that the age category required additional 

breakdowns to allow for more options and targeting, if needed. For results from smaller mine 

sites, NIOSH researchers tended to collapse some of these categories to allow for statistical 

testing.

Recruitment and Data Collection

NIOSH received approval from the Office of Management and Budget in February 2016. Data 

collection occurred between February 2016 and March 2018. Individual mines were initially 

recruited through research contacts. Once initial data collection with the first company was 

completed and pilot results were communicated during various mining trade and conference 

presentations, subsequent participating sites began to contact NIOSH to participate. Although 

NIOSH did not have to engage in extensive recruiting due to industry interest, the final sample 

rendered participation from three common subsectors as well as a larger sample than anticipated.

Upon being contacted by a corporate H&S leader, mine operator, or H&S manager, a mutually 

agreed-upon time was chosen to travel to the mine and administer the survey. If an upcoming 

Mine Safety and Health Administration (MSHA) annual refresher training (ART) was scheduled, 

researchers often visited the mine because everyone was together at one time. If an upcoming 

ART or other training was not on the mine’s schedule soon, researchers worked with the mine to 

pick one or two days that were convenient to attend pre-shift safety meetings to collect the 

survey data. In this scenario, researchers would often be present at the mine location all day to 

catch varying shift rotations.

Mine management and hourly workers were briefed about the purpose of the survey and told that 

their responses would be anonymous and not be seen by their supervisors. Everyone was given 

the option to voluntarily participate and given contact information of the principal investigator 

with follow-up questions. To the authors’ knowledge, no one refused to participate. The survey

took approximately 15 minutes for participants to complete.

Researchers collected the hard copy surveys and subsequently they were entered into a Statistical 

Package for the Social Sciences (SPSS) file for cleaning and analysis. In some cases, entire 

surveys were discarded if it was clear that participants were not reading the questions (i.e.,

responding with all 6’s or all 1’s). This did not occur often—in general, a few surveys per mine 

site, which was usually about two to three percent of the sample at a mine site. Additionally, any 

responses that were not answered within each survey were coded as “missing data” during the 

data cleaning process.
14

Survey Participants

Participants consisted of 2,683 workers—both salaried and hourly—at 39 mine sites throughout 

17 states. The mines represented nine major companies and three mining subsectors (i.e., coal; 

stone, sand and gravel; and industrial minerals). To the authors’ knowledge, everyone who was 

present on-site during data collection completed the survey, including office workers and 

management. The breakdown of participation by subsector is in Table 4. The remaining 

demographic characteristics of the sample are reported in Tables 5–8.

Table 4. Breakdown of participation by mined subsector

Mine Subsector Survey Count Percent of Sample Mine Count

Coal 358 13 2

Industrial minerals 907 34 9

Stone, sand, and gravel 1,418 53 28

Table 5. Demographic characteristics of participants

Demographic Characteristics Survey Count Percent

Gender (72 missing) 8,673 8,673

Male 2,438 93.4

Female 173 6.6

Job classification (94 missing)

Salaried 569 22.0

Hourly 2,020 78.0

Age range (79 missing) 8,673 8,673

18–24 134 5.1

25–34 523 20.1

35–44 596 22.9

45–54 730 28.0

55–64 561 21.5

65+ 60 2.3

Highest level of education: (77 missing) 8,673 8,673

Less than high school 75 2.9

High school 1,532 58.8

Associate’s degree/Trade certificate 686 26.3

Bachelor’s degree 244 9.4
15

Demographic Characteristics Survey Count Percent

Master’s degree or higher 69 2.6

Family mining history: (135 missing) 8,673 8,673

First-generation mineworker 1,682 66.0

Multi-generation mineworker 866 34.0

Table 6. Experience in current job (69 missing)

Experience level Survey Count Percent

Under 1 year 371 14.2

1–5 years 723 27.7

6–10 years 438 16.8

11–15 years 327 12.5

16–20 years 204 7.8

20+ years 551 21.1

Table 7. Experience at current mine (155 missing)

Experience at Current Mine Survey Count Percent

Under 1 year 354 14.0

1–5 years 574 22.7

6–10 years 407 16.1

11–15 years 351 13.9

16–20 years 217 8.6

20+ years 625 24.7

Table 8. Experience in the mining industry (106 missing)

Experience in Mining Industry Frequency Valid Percent

Under 1 year 239 9.3

1–5 years 470 18.2

6–10 years 448 17.4

11–15 years 397 15.4

16–20 years 245 9.5

20+ years 778 30.2
16

Data Analysis

Within the 58-item survey, eight of the items were reversed-scored—a common approach to 

ensure participants were alert and paying attention to the questions [Devellis 2012]. Using this 

approach, NIOSH researchers were able to easily eliminate surveys for those people who were 

not reading the questions or not taking the time to respond. In general, anywhere from 0–5 (0%–

3%) surveys at each participating mine were eliminated using this screening approach. These

negatively worded items were reverse-scored prior to analysis, during the data cleaning stage, to 

ensure that their directionality matched the other 50 items in the survey. 

To answer the first research objective (i.e., determine benchmarks of each safety climate 

construct), the average score for each item and construct was calculated. Given that the 

dependent variables were skewed, Kruskal-Wallis tests, a non-parametric statistical test, were 

used to determine if significant differences existed among commodities. The Kruskal-Wallis 

allowed researchers to determine if the subsectors were statistically different from each other.

Establishing Benchmarks using Construct Averages

The use of benchmarking was similar to that of typical psychometric survey studies [i.e., Healey 

et al. 2012; Mearns et al. 2001a; Miller and Cox 1997]. Specifically, the use of means and 

frequency distributions were used as benchmarking tools [Stapenhurst 2009]. The means allowed 

interpretation at the aggregate level and comparison of individual sites with the overall average. 

Therefore, the mean was calculated for each of the constructs. High scores (6) represented 

favorable ratings and low scores (1) represented negative views of the construct being measured.

Mean = (∑xi) /n

For the purposes of this study, the benchmarks enable organizations to prioritize safety-related 

deficiencies for intervention. Additionally, organizations are able to compare constructs within 

their safety climate to those of other subsectors or the overall average. This comparison 

facilitates a response to areas that scored “lower” at respective companies.

Frequency distributions were reported at the aggregate level as well. These two approaches 

occurred for the overall sample as well as for each of the three participating subsectors. This 

allowed researchers to make visual and statistical comparisons of the difference in averages 

[Healey et al. 2012].

Using Relative Weights to Identify Significant Predictors

The second and third objectives (i.e., determine the most influential personal and organizational 

constructs on workers’ H&S proactivity and compliance) were addressed using relative weights 

analysis (RWA) [Johnson 2000; Tonidandel et al. 2009; Tonidandel and LeBreton 2011]. In the 

context of multiple regression, RWA was used to examine the relative contribution of the six 

organizational and four personal safety climate constructs in predicting worker H&S proactivity 

and compliance, knowledge, motivation, near misses, and other incident outcomes. RWA is used 

in situations where the relative importance of numerous correlated predictors is of interest. The 

method decomposes the total variance in a dependent variable that is explained by a set of 

correlated predictors into an accurate set of weights that reflect the proportional contribution of 

each of the predictors in the model [Tonidandel and LeBreton 2011]. In this context, RWA 
17

methodology uses a series of orthogonally transformed regressions to determine the importance 

of each predictor in the prediction of the dependent variables.

Prior to the development of RWA, the relative importance of predictors could be estimated by 

examining and comparing the standardized regression coefficients for a set of predictors. 

However, this method does not account for the potential inter-correlations among the set of 

predictors. Using relative weights solves the inter-correlation problem by transforming the set of 

predictors so that they are uncorrelated prior to examining their relative importance [Johnson 

2000; Tonidandel at al. 2009; Tonidandel and LeBreton, 2011]. This was a necessary step to 

ensure a reliable analysis. Researchers used processes defined and illustrated by Tonidandel and 

LeBreton [2011] to derive the relative weights for each of the 10 predictors included in the 

current study. Analysis was done in R using the macro developed by Tonidandel and LeBreton 

[2015] (http://relativeimportance.davidson.edu/). This developed routine uses a bootstrapping 

approach to derive confidence intervals and tests of significance for each of the predictor’s 

relative importance parameters.

Results

Results by question for the overall sample and by commodity are listed in Appendix C, and the 

results by question for the coal, stone, sand, and gravel (SSG), and industrial minerals subsectors 

are listed in Appendices D, E, and F. For each question, the frequency distribution, or aggregate 

measurement for each category, is listed. The reporting of results back to mine sites in this 

fashion was desirable for the mine’s benefit. For example, while an average could have resulted

in a high 4, trending toward agreement, there may have been a large percentage of a mine’s

sample disagreeing with certain construct items. The percentages gave mines more information 

and allowed them to target specific interventions not only by construct, but by question. For 

these reasons, both the mean and frequency distribution communicated different and very 

important pieces of information for benchmarking purposes.

Additional analyses have also been completed and published to examine differences in certain 

demographics and impact on workers’ perceptions and H&S performance. One paper [Haas et al. 

2018b] examined the differences in safety climate perceptions between mining companies who 

promote autonomous work environments versus those who maintain more general management. 

Other papers [Haas et al. 2019; Hoebbel et al. 2019] have examined differences in workers’ 

experience levels and impact on risk tolerance, compliance, and overall H&S performance in the 

industry. Finally, analyses have examined the role of demographic variables in workers’ risk 

tolerance, sense of control, and experiencing near miss incidents [Haas and Yorio 2019]. Results 

found that education was the only significant variable impacting near miss experiences.

Safety Climate Benchmarks in the Mining Sector

In this section, initial benchmarking data for each safety climate construct are reported and 

established, including the dependent variables measured within the survey. The figures within 

this section visually show the benchmarks, or averages, for the overall sample and within each 

subsector. The figures show the results on the 1 to 6 Likert-based scale. 
18

Proactivity: Survey items 1–5

The averages for proactivity among each subsector were close to the overall sector average. As 

shown in Figure 1, coal and industrial minerals rendered a slightly lower average (4.85 on a sixpoint scale) than the overall average, while SSG came out with a slightly higher average (4.98). 

These averages, all nearing 5 or “agree,” indicate that workers perceive themselves to be 

proactive and make efforts within their control to identify, report, and fix potential hazards. The 

omnibus Kruskal-Wallis test showed a statistically significant difference across the three mining 

subsectors (2, n = 2,646) =18.42, p < 0.001. Follow-up, pairwise comparisons using the MannWhitney test and Bonferroni adjusted significant level (0.05/3 = 0.016667) suggested that SSG 

was significantly different from both coal and industrial minerals (p<0.001). Coal and industrial 

minerals were not significantly different from each other (p=0.89). However, with the minimal 

deviation in averages, the differences are likely not practically significant. The 95% confidence 

intervals are: overall (4.88–4.95); coal (4.76–4.94); industrial minerals (4.79–4.91); and SSG 

(4.88–4.95). 

Figure 1. Proactivity averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial minerals

Coal

Overall

4.98

4.92

4.85

4.85
19

Compliance: Survey items 6–9

Figure 2 shows that the average for compliance was 5.26, which is a positive average and shows 

workers’ strong perceptions of their rule-following practices on the job. As shown in Figure 2, 

coal is more than a quarter point lower than the average (4.95), whereas industrial minerals and 

SSG are both slightly higher than the average (5.31). The Kruskal-Wallis ((2, n = 2,634) = 60.68, 

p < 0.001) indicates that these differences among the three subsectors are statistically significant. 

Follow-up, pairwise comparisons using the Mann-Whitney test and Bonferroni adjusted 

significant level suggested that coal was significantly different from both SSG and industrial 

minerals (p<0.001). SSG and industrial minerals were not significantly different from each other 

(p=0.70). Notably, it appears that the compliant practices of coal miners may be significantly 

lower than the other two subsectors.

Figure 2. Compliance averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Coal

Overall

5.26

4.95

5.31

5.31

Industrial minerals

Stone, 

sand,

gravel
20

Organizational Support for Health and Safety: Survey items 23–25

For organizational support for H&S, Figure 3 shows some deviation among the subsectors. The 

overall average was 4.36, trending lower but still in the positive range. The coal subsector

produced an average of 4.05, barely over the “somewhat agree” response. The industrial minerals 

subsector reported the highest average at 4.53. The Kruskal-Wallis test ((2, n = 2,618) = 53.32, p

< 0.001) indicates that these differences among the three subsectors are statistically significant. 

Follow-up, pairwise comparisons using the Mann-Whitney test and Bonferroni adjusted 

significant level suggested that each of the commodities were significantly different from one 

another at the p<0.001 level. As shown in Appendix B, the questions within this scale focused on 

ignoring H&S rules to get the job done and feelings of impossible production pressures.

Figure 3. Organizational support for health and safety averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial minerals

Coal

Overall

4.05

4.53

4.33

4.36
21

Supervisor Support for Health and Safety: Survey items 29–31

Perceptions of supervisor support for H&S were consistent among subsectors, with the overall 

average being 4.85. Figure 4 shows that all three subsectors are within approximately one-tenth 

of each other. So, although the Kruskal-Wallis results are statistically significant ((2, n = 2,644)

= 8.99, p < 0.011), with the minimal deviation in averages with the minimal deviation in 

averages, these differences may not be practically significant. Follow-up, pairwise comparisons 

using the Mann-Whitney test and Bonferroni adjusted significant level suggested that coal was 

not significantly different from SSG (p=0.65) or industrial minerals (p=0.02). SSG was 

significantly different from industrial minerals (p=0.006).

Figure 4. Supervisor support for health and safety averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial

minerals

Coal

Overall

4.80

4.92

4.82

4.85
22

Supervisor Communication: Survey items 32–38

Perceptions of supervisor communication resulted in larger differences among subsectors. The

SSG subsector revealed an almost identical average to the overall sample (4.76) whereas coal 

was lower (4.58) and industrial minerals was higher (4.80). Figure 5 shows these results, which 

were also significant ((2, n = 2,604) = 13.80, p < 0.001). Follow-up, pairwise comparisons using 

the Mann-Whitney test and Bonferroni adjusted significant level suggested that coal was 

significantly different from both SSG and industrial minerals (p<0.001) and industrial minerals

and SSG were not significantly different from each other (p=0.24).

Figure 5. Supervisor communication about H&S averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial minerals

Coal

Overall

4.58

4.80

4.78

4.76
23

Coworker Communication: Survey items 26–28

The averages for coworker communication within each subsector were close to the overall 

average of 5.05. As shown in Figure 6, the industrial minerals subsector had the lowest average 

(4.90) whereas the coal and SSG subsectors were closer and even slightly above the average.

These averages, all nearing 5 or “agree,” indicate that workers perceive themselves to be 

communicative with each other about H&S on the job. It is possible that for the industrial 

minerals subsector, the nature of the work is sometimes more likely to involve the individual 

working alone and to be more scattered across an operation’s surface. So, the opportunity to 

watch out for other coworkers or alert them about a potential hazard may not exist as often as in 

the other subsector. The Kruskal-Wallis test ((2, n = 2,658) = 10.27, p < 0.006) indicates that 

these differences among the three subsectors are statistically significant. Follow-up, pairwise 

comparisons using the Mann-Whitney test and Bonferroni adjusted significant level suggested 

that industrial minerals was not significantly different from coal or SSG (p=0.03 and p=0.24, 

respectively). Coal and SSG were significantly different at the p<0.001 level but, with the 

minimal deviation in averages, are likely not practically significant.

Figure 6. Coworker communication about H&S averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial minerals

Coal

Overall

4.90

5.05

5.09

5.05
24

Worker Engagement: Survey items 39–42

The overall average for worker engagement was 4.53. As shown in Figure 7, the industrial 

minerals sector had the highest average (4.64) with the SSG subsector not far behind (4.54). The 

coal subsector was almost half a point lower than these other averages. It is possible that for the 

coal subsector, more processes are regulated than for the other two, so participation in H&S rules 

may not always be an option. Depending on the relative weight of worker engagement on worker 

proactivity and compliance, it may be beneficial for coal practitioners to identify additional 

opportunities to involve workers in health and safety procedures and decision making on site. 

The Kruskal-Wallis test was (2, n = 2,640) = 43.69, p < 0.001), which indicates that these 

differences among the three subsectors are statistically significant. Follow-up, pairwise 

comparisons using the Mann-Whitney test and Bonferroni adjusted significant level suggested 

that coal was significantly different from both industrial minerals and SSG at the p<0.001 level. 

Industrial minerals and SSG, however, were not significantly different (p=0.07).

Figure 7. Worker engagement averages overall and

by commodity overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial minerals

Coal

Overall

4.16

4.64

4.54

4.53
25

Health and Safety Training Adequacy: Survey items 49–51

The overall average for training adequacy was 5.15. As shown in Figure 8, the industrial 

minerals subsector had a visually higher average (5.32) with the SSG subsector following at 5.09 

and then coal at 4.96. The Kruskal-Wallis test was (2, n = 2,625) = 53.55, p < 0.001), which

indicates that these differences among the three commodities are statistically significant.

However, all averages are high, indicating that most all workers have a positive view of current 

H&S training. Follow-up, pairwise comparisons using the Mann-Whitney test and Bonferroni 

adjusted significant level suggested that industrial minerals was different from both coal and 

SSG at the p<0.001 level. Coal and SSG were not significantly different from each other with the 

p value being right above the Bonferonni adjusted level of significance, p=0.017.

Figure 8. Health and safety training adequacy averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial

minerals

Coal

Overall

4.96

5.32

5.09

5.15
26

Worker Adaptability: Survey items 52–54

Adaptability did not have much variance among the subsectors, all being in the average 4-point 

range. Figure 9 shows the similar averages for the mining sector and the three subsectors. The 

Kruskal-Wallis test was (2, n = 2,622) = 1.82, p =0.403), which indicates that these differences 

among the three commodities were not statistically significant. Follow-up, pairwise comparisons 

using the Mann-Whitney test confirmed the findings of the omnibus test. As RWA tests reveal 

later, adaptability also did not demonstrate significant differences for these groups.

Figure 9. Worker adaptability averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial minerals

Coal

Overall

4.63

4.69

4.71

4.69
27

Risk Tolerance: Survey items 19–22

The results for risk tolerance (Figure 10) showed statistical differences among the subsectors ((2, 

n = 2,662) = 37.50, p < 0.000). The industrial minerals subsector (5.30) and SSG subsector

(5.33) were both slightly above the average whereas the coal subsector was slightly below (5.06). 

Follow-up, pairwise comparisons using the Mann-Whitney test and Bonferroni adjusted 

significant level suggested that coal was significantly different from both industrial minerals and 

SSG at the p<0.001 level. Industrial minerals and SSG were not significantly different (p=0.39). 

However, all averages were high, indicating that a large percentage of the mining workforce does 

not regularly take risks on the job and has a low tolerance for risks on site. Of interest in this 

construct scale was often one question that asked workers if they took risks regularly. Within the 

overall sample, about 12% of participants reported taking risks on a regular basis. This prompted 

some companies to address risk tolerance, as highlighted in the Discussion section.

Figure 10. Worker risk tolerance averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial minerals

Coal

Overall

5.06

5.30

5.33

5.28
28

Worker Sense of Control: Survey items 10–13

The results for sense of control are shown in Figure 11. The results demonstrated statistical 

differences among the subsectors ((2, n = 2,642) = 7.11, p < 0.029). Follow-up, pairwise 

comparisons using the Mann-Whitney test and Bonferroni adjusted significant level suggested 

that only coal and industrial minerals were significantly different from each other (p=0.008). All 

of the averages were grouped close together, between 4.57 and 4.68. This construct resulted in 

the lowest average for the internal set of safety climate constructs, mainly due to workers’ 

responses in that they do not have control over certain health and safety outcomes or work 

decisions on site. Specifically, almost 47% of participants reported most H&S problems not 

being within their control.

Figure 11. Worker sense of control averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial minerals

Coal

Overall

4.57

4.68

4.64

4.64
29

Worker Thoroughness: Survey items 14–18

Thoroughness averages (Figure 12) showed statistical differences among the subsectors ((2, n = 

2,625) = 13.46, p < 0.001). Follow-up, pairwise comparisons using the Mann-Whitney test and 

Bonferroni adjusted significant level suggested that only coal and SSG were significantly 

different from each other (p<0.001). Again, the averages were grouped close together, between 

5.11 and 5.25. This construct rendered higher averages than most internal safety climate 

constructs, indicating that workers feel confident in their precision and duty to complete their job 

tasks. This high self-assessment of thoroughness is assuring, as the RWA results reveal 

thoroughness as a heavily weighted predictor for worker H&S performance and outcomes.

Figure 12. Worker thoroughness averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial minerals

Coal

Overall

5.11

5.19

5.25

5.21
30

Health and Safety Knowledge

Health and safety knowledge served as a proximal predictor to worker H&S performance and,

therefore, was treated as a dependent variable in the subsequent RWAs. The benchmark results 

did show statistical differences among the subsectors ((2, n = 2,623) = 32.33, p < 0.001). Followup, pairwise comparisons using the Mann-Whitney test and Bonferroni adjusted significant level 

suggested that coal was significantly different from both industrial minerals and SSG at the 

p<0.001 level. Industrial minerals and SSG were not significantly different p=0.53.The lowest 

average was the coal subsector with 5.04. However, this average is still very high, being in the 

“agree” range and indicating that workers feel like they have a sense of how to use equipment 

and execute the procedures necessary on the job to stay safe. Figure 13 shows these averages.

Figure 13. Health and safety knowledge averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial minerals

Coal

Overall

5.04

5.27

5.30

5.26
31

Health and Safety Motivation 

Health and safety motivation was the other proximal predictor to worker H&S performance and,

therefore, was treated as a dependent variable in the subsequent RWAs. The results are shown in 

Figure 14, revealing statistical differences among the commodities ((2, n = 2,638) = 12.05, p <

0.002). Follow-up, pairwise comparisons using the Mann-Whitney test and Bonferroni adjusted 

significant level suggested that coal was significantly different from both industrial minerals and 

SSG at the p<0.001 level and industrial minerals and SSG were not different from each other.

However, with all the averages being extremely skewed to the right and close to the average, the 

practical difference is likely non-existent. 

Figure 14. Health and safety motivation averages overall and by subsector.

Strongly

disagree

Disagree Somewhat

disagree

Somewhat

agree

Agree Strongly

agree

Stone,

sand,

gravel

Industrial minerals

Coal

Overall

5.55

5.64

5.64

5.63
32

Although these results provide a benchmark for each construct or factor represented within the 

survey, assumptions of benchmarking studies indicate that the “better” or “higher” performing 

workers more often contribute to current benchmarks [Healey et al. 2012]. Therefore, it is 

possible that the highest scores reported within the surveys could be slightly inflated and should 

be taken into consideration when interpreting these results.

Differences among Subsectors

As the above breakdown by subsector illustrated, coal workers often had lower perceptions than 

those workers in SSG or industrial minerals, although not all were statistically significant. For 

example, there was a mean difference of 0.48 when comparing perceptions of organizational 

support between coal miners and industrial minerals miners. It is important to note when 

interpreting these results that, in general, the averages for each scale among each subsector is 

relatively high. That is, even though the coal subsector experienced lower averages, the averages 

tended to still be in the “somewhat agree” to “agree” range. Even so, with this trend in the 

results, it is important to consider that even small differences on a perception scale can equate to 

meaningful differences at the organizational level as well as in individual-level outcomes.

This is the first study (to the authors’ knowledge) in which a breakdown of mining subsector 

differences has been reported in the United States. In a recent systematic review of safety 

outcomes and H&S performance in high-risk industries, underground mining was not included 

because the commodity was said to represent highly specific risks [Cornelissen et al. 2017]. 

However, there is some overlap in results with a large safety culture initiative in the Australian 

mining industry surveyed coal and gold mine workers, where coal miners at the 

hourly/contractor level were significantly more negative [SAFEmap 1999].

Although it is difficult to speculate all the reasons why U.S. coal miners reported lower 

perceptions in the current study, underground coal mining has been reported as more complex 

and dynamic than other types of mining and specifically, has been encouraged—but not 

required—to go beyond the mandated rules and regulations, and adopt comprehensive 

occupational HSMS [Zhou et al. 2018]. However, research has argued that the diffusion of 

HSMS and specifically, risk-based processes, have been slow to take hold in the coal subsector 

[Yang 2012]. Therefore, when discussing the weighted results and takeaways in the subsequent 

sections, management and practitioners representing the coal mining industry may be able to 

glean more in the areas of worker empowerment and leadership. 

Significant Predictors of Workers’ H&S Performance

The relative weights regressions were used to determine which factors were the most influential 

in worker proactive and compliant H&S performance. This analysis includes the ranking of each 

factor based on its contribution to R2. R

2 is the percentage of the variation in the dependent 

variable(s) that is explained by each factor when determining the overall contribution to worker 

proactivity and compliance. For easier interpretation, rather than present the raw relative weights 

that sum to the observed value of R2, the rescaled relative weights (RS-RW) are presented. The 

RS-RW percentages for each predictor within the tables sum to 100 percent.
33

Predictors of Proactivity

This first model showed that all 10 safety climate constructs were significant predictors of 

worker proactivity. The overall model fit was R2 = .32, or 32.24%. According to Cohen [1988],

this R

2

indicates a large effect size and shows promising areas of inquiry within certain factors. 

Table 9 lists the RS-RW of each construct.

Table 9. Weighted impact of safety climate constructs on worker proactivity

using overall sample. All 10 constructs are significant at the p = .05 level

Construct Rank Proactivity RS-RW (%)

Thoroughness 20.76

Sense of control 17.06

Risk tolerance 13.16

Worker engagement 12.36

Coworker communication 8.88

Supervisor communication 7.36

Adaptability 7.14

Supervisor H&S support 6.07

H&S training 5.65

Organizational H&S support 1.57

For workers’ proactivity, or their willingness to take initiative and report or fix H&S issues, a 

personal sense of thoroughness and control over their job tasks were the highest predictors at 21 

and 17%, respectively. In addition, workers’ personal levels of risk tolerance (13%) and their 

involvement or engagement in H&S activities on site (12%) were also greater predictors of 

proactivity.

Appendices G, H, and I show the ranking of the factors within each subsector. These models 

show that, although most if not all constructs are statistically significant, some had less of a 

weighted contribution to the subsector model. Thoroughness was either the first- or secondlargest predictor for the three subsectors, while risk tolerance and sense of control also remained 

at the top. Of interest is that worker engagement was the most prevalent organizational factor 

that influenced workers’ proactivity and was even the highest-weighted construct within the 

industrial minerals subsector (21%). Similarly to the overall model, coworker communication 

remained a steady contributor to worker proactivity across the industry subsectors, ranging from

8%–11%.

Predictors of Compliance

The compliance model showed that all 10 safety climate constructs were significant predictors of 

worker compliance. The overall model fit was R2 = .46, or 46.70%. According to Cohen [1988],

this R2indicates a large effect size and shows promising areas of inquiry within certain factors. 

Table 10 lists the RS-RW of each construct.
34

Table 10. Weighted impact of safety climate constructs on worker compliance

using overall sample. All 10 constructs are significant at the p = .05 level

Construct rank Compliance RS-RW (%)

Risk tolerance 30.60

Thoroughness 23.10

Coworker communication 10.50

Sense of control 8.70

Supervisor communication 5.50

Worker engagement 5.40

H&S training 5.30

Supervisor H&S support 4.60

Organizational H&S support 3.80

Adaptability 2.60

Looking at compliance, workers’ risk tolerance was the predominant predictor at almost 31%. In 

addition, workers’ thoroughness (23%) and then coworker communication (11%) were strong 

predictors of workers’ compliant behaviors. H&S training, although a significant predictor, only 

contributed about 5% to the entire model. Additionally, organizational support for H&S only 

contributed about 4%. These areas typically receive ample attention on mine sites; however, the 

results indicate that a greater focus on workers’ abilities to assess and communicate about risks 

during day-to-day operations may be more important in supporting workers’ safety practices on 

the job.

Appendices G, H, and I show the ranking of the factors within each subsector. Of importance to 

the mining sector is that risk tolerance remained the largest predictor for all three subsectors, 

ranging from 26%–31%, showing that workers’ risk tolerance or avoidance perceptions 

significantly contribute to their likelihood of following H&S rules on the job. Thoroughness was 

the second highest predictor for all three subsectors, ranging from 18%–26%. For compliance, 

coworker communication remained as a significant, noteworthy contributing variable ranging 

from 8%–13%. For the coal subsector, however, supervisor communication had a higher weight 

at 9%.

Predictors of H&S Knowledge and Motivation

Because knowledge and motivation are primary factors in precede-proceed models that lead to 

behavior change [Li et al. 2009; Noar and Zimmerman 2005], determining whether or not

different factors emerged within these models was deemed important for mine practitioners to 

know. Tables 11 and 12 show the models for knowledge and motivation. The overall fit for the 

knowledge model was R

2 = 0.5 or 50.03%. The fit for the motivation model was R2 = 0.39 or 

39.74%. Tables 11 and 12 show the percentage of the variation that is explained by each factor 

when determining the overall contribution to workers’ knowledge and motivation.
35

Table 11. Weighted impact of safety climate constructs on worker H&S

knowledge. All 10 constructs are significant at the p = .05 level

Construct Knowledge RS-RW (%)

Thoroughness 14.74

Worker engagement 13.15

H&S training 12.29

Coworker communication 12.17

Supervisor communication 11.30

Risk tolerance 10.57

Adaptability 9.65

Sense of control 7.99

Supervisor H&S support 5.97

Organizational H&S support 2.16

External constructs contributed more to the knowledge model than the previous H&S

performance models. Particularly, in both the knowledge and motivation models, H&S training 

had a larger weight. Although training significantly and heavily contributed to workers’ 

knowledge and motivation, the proactivity and compliance models show that it (training) does 

not necessarily translate to behavior change. The factors that consistently rendered high 

predictive utility throughout the models such as risk tolerance, thoroughness, worker 

engagement, and coworker communication can be considered factors that are critical to 

emphasize during site activities. Potential efforts to improve and maintain these predictive 

factors will be discussed later.

Table 12. Weighted impact of safety climate constructs on worker

motivation. All 10 constructs are significant at the p = .05 level

Construct Motivation RS-RW (%)

Thoroughness 18.35

Risk tolerance 17.52

H&S training 16.96

Adaptability 12.00

Sense of control 9.16

Coworker communication 8.77

Supervisor communication 5.75

Worker engagement 5.34

Supervisor H&S support 3.65

Organizational H&S support 2.50
36

Significant Predictors of Workers’ H&S Outcomes

The final RWA models included the four types of incident occurrences that were measured. For

these four items, frequencies were low, considering that most incidents, especially days lost, are 

not prevalent in the industry much less at individual participating mine sites. However, being 

able to compare the predictor utility of the safety climate constructs in incident outcomes has 

merit in terms of where an organization needs to focus HSMS efforts to prevent future accidents

[Robson et al. 2007; Yorio et al. 2015]. Table 13 shows that together, the safety climate 

constructs predicted approximately 8% (R2 = 8.26%) of near misses experienced; 6% (R2 = 

5.72%) of first aid incidents experienced; 7% (R2 = 7.29%) of incidents experienced that required 

medical treatment; and 6% (R2 = 6.13%) of days lost among participants. This model still 

produced several statistically significant results although not as many as the prior models. The 

significant predictors are marked with an asterisk.

Table 13. Impact of safety climate constructs on worker H&S outcomes

Construct

Near misses

RS-RW (%)

First aid

RS-RW (%)

Med. Treatment

RS-RW (%)

Days Lost

RS-RW (%)

Organizational 

H&S support

36.02* 34.59* 36.71* 36.99*

Supervisor H&S 

support

8.12* 3.82 3.53* 4.42*

Supervisor 

communication

2.84 1.97 2.68 3.73

Coworker 

communication

1.38 1.69 1.79 1.45

Worker 

engagement

4.30* 2.56 4.41* 4.59*

H&S training 14.45* 15.13* 12.56* 13.27*

Sense of control 2.31 3.05 2.94* 3.79

Thoroughness 11.16* 19.35* 20.36* 21.81*

Risk tolerance 18.96* 15.95* 11.19* 8.43*

Adaptability 0.46 1.86 3.80* 1.52

*Statistically significant at the p = .05 level.

Organizational support for H&S was the largest predictor (34%–36% of the variance) of each 

incident outcome. This construct was significant for the previous models but had the lowest 

weighted impact on H&S performance, knowledge, and motivation. The individual questions 

within the organizational support construct relate to going around safety rules to get the job done

or feeling pressure to produce. The current results indicate that ignoring safety procedures and 

feeling pressured to cut corners can significantly influence a near miss or even an incident at 

some point in time.
37

Training, thoroughness, and risk tolerance remained as large and significant predictors of the 

four outcome variables. Also, supervisor support predicted 8% of the total variance of near 

misses, indicating that supervisors’ attention to safety details on site may impact workers’ 

willingness to acknowledge and potentially report a near miss. Subsector results are presented in 

Appendices G, H, and I and indicate the importance of the organizational constructs in 

preventing lagging indicators. Although there were fewer constructs that achieved statistical 

significance in these outcome models, the constructs that were significant contributed large

weights, providing a clear path for practitioners to focus on.

Discussion—Improving Safety Management Practices

The results provide new insights in how to improve workers’ H&S on the job while supporting

what research has found. Although previous research has established the influence of both 

organizational and individual factors on H&S performance [e.g., Cox and Flin 1998; 

Guldenmund 2000; Hofmann et al. 1995; Mearns et al. 2003], research that shows the impact of 

these two areas together on worker H&S performance has not been done. The results provide the 

mining industry with additional areas of specific focus and the value of focusing on individual 

factors when trying to make improvements on the organizational level. For example, similar

occupational H&S studies (not specific to mining) have shown that management support or 

management commitment is the strongest predictor of worker behaviors and injury outcomes

compared to other safety climate constructs [Beus et al. 2010; Christian et al. 2009; DeJoy et al. 

2010]. While management support and communication were found to be significant predictors as 

other studies have shown [e.g. Clarke 2010; Nahrgang et al. 2011], they were certainly not the 

strongest predictors for any of the outcomes measured. However, the current study did show that 

organizational support was the most significant predictor for near misses and incident outcomes.

Kirwan [1998] discusses safety management as the actual practices, roles, and functions 

associated with remaining safe on the job. These practices, which can be a sub-system of the 

HSMS, are meant to be integrated into the organization’s overall procedures and strategies in an 

effort to control hazards and respond to risks [Labodova 2004; Vinodkumar and Bhasi 2010]. 

Further, safety management practices have been regarded as an antecedent, or predictor, of an 

organization’s safety climate [Vinodkumar and Bhasi 2010]. As a result, gleaning ways to 

improve safety management practices, based on the current safety climate benchmarks and 

weighted analyses, can function to improve workers’ perceptions of the safety climate later. 

Consequently, this section focuses on specific safety management practices that can be employed 

by organizations and site leadership to improve specific organizational and individual factors of 

interest.

Notably, the results showed that personal constructs were the most influential in predicting 

workers’ H&S performance. Other research has shown consistent relationships between personal 

states and safety performance. For example, studies [Beus et al. 2015; Clarke and Robertson 

2005] found that conscientiousness (also known as thoroughness), was negatively associated 

with unsafe work acts. These researchers also found that risk tolerance and specifically, 

sensation-seeking personalities, are more strongly related to unsafe behavior. However, 

uncovering the roles of person-based factors among workers, especially in relation to 

organizational factors, has not yet been achieved.
38

These results also show the value of organizations accounting for and responding to both the 

organizational and personal factors where possible. In most cases, addressing these two areas 

may occur simultaneously due to their interdependencies. To that end, the discussion provides 

examples of interventions that can be disseminated on an organizational level to influence 

workers’ personality-based factors on the job. Examples provided stem from actual interventions 

developed and implemented at mine sites to improve constructs of their site-specific results and 

are provided as prompts to assist other H&S practitioners.

Going beyond Annual Refresher Training 

A similar, primary way in which the mining industry prepares workers to work both proactively 

and reactively on the job are via standards developed by the Mine Safety and Health 

Administration (MSHA) that include provisions on who needs to be trained, how much training 

is needed, who can provide training, and subject areas to be covered. These requirements are 

included in the Code of Federal Regulations (30 CFR § 48) on training and retraining of 

underground coal workers. A similar regulation, Part 46, is in place for metal/nonmetal. Within 

the current results, it is safe to assume that most of this new employee, annual refresher, and 

other task training is adequate, considering the high benchmark as well as its significant 

contribution to worker knowledge within the study. Although H&S training emerged as a strong 

predictor of workers’ knowledge on the job, it had a smaller weight on workers’ actual H&S 

performance in terms of proactivity and subsequent decision making.

This is an important point to emphasize considering that in many cases organizations may 

assume that more safety training is an answer and can encourage safer work practices. For 

example, some argue that if training is required by an entity such as MSHA or OSHA, then it 

must be done and can be used as a quick solution to worker performance issues [Machles 2007]. 

However, more training does not necessarily account for the individual factors measured within 

the survey such as risk tolerance and, ultimately, safety decisions. Some even argue that using 

training to address H&S performance or compliance issues is an ineffective use of resources 

[Machles 2007]. Although a strong statement, limited research has found that the quality of 

safety training is more important than quantity [Burke et al. 2006] and, specific to mining, 

research has shown that increased hours of workplace safety training—in its generic and oftenused form—does not impact workers’ tolerance of risks and subsequent decision making on the 

job [Lehmann et al. 2006].

With the current results supporting that training is not a strong predictor of worker decision 

making, emphasizing other elements of an organization’s HSMS remains critical for the mining 

industry. Specifically, management may need to focus on improving workers’ opportunities and 

involvement to increase workers’ sense of control, as well as actual control, and confidence.

Additionally, enhanced communication with workers may be necessary in order to identify what 

the root causes of certain problems are, such as an equipment issue or even peer pressure 

[Machles 2007]. For instance, research has shown that the transfer of any training into practice 

will not occur if workers do not have adequate levels of self-efficacy and control as well as 

support from their management [Grossman and Salas 2011]. Therefore, rather than work to 

“provide more training,” the focus should be on improving the level of follow-up and 

communication that starts when the training commences and continues thereafter. Dated research 

has argued that people often forget 90% of what they learned within 3–6 days, unless learning is 
39

reinforced with multiple repetitions [Ebbinghaus 1913]. However, more recent research shows 

that this percentage of forgetfulness is highly variable based on workers’ preexisting knowledge 

and their motivation [Thalheimer 2010].

Regardless of the percentage of content that workers remember, it is obvious that efforts need to 

be made within the organization to promote H&S practices and instill a sense of autonomy to 

motivate workers to make their own decisions [Haas et al. 2018b, NIOSH 2016]. This can be 

done by first, including training on the development of soft skills (i.e., communication) among 

the workforce as well as empowerment training to ensure that workers have the ability and 

support to take action prior to a supervisor’s approval. Examples of how some companies have 

tried to address soft skills during trainings and subsequently on the job are discussed below.

Developing workers’ soft skills

The transfer of any mandated training, such as MSHA’s annual refresher courses, may be more 

useful if the training itself does a better job of improving workers’ internal factors as a means to 

sustain their communication and motivation levels. A CRH company, Oldcastle Materials Group, 

made an effort to do just that; the company updated its ARTs to not only include the required 

MSHA topics, but also modules including types of communication, improving worker

communication, leadership, teams, teambuilding, teamwork, and risk tolerance.

It appears that, for this small case group, participants appreciate when trainings go beyond the 

basic H&S content that has become the norm. For example, in an evaluation of the new softskills ART content outlined above, workers listed what they liked best about the training 

program. The most common responses aligned with the following topic areas:

• Learning about communication

• Leadership training

• The bar just got moved higher

• Kept the class interactive

• Interaction of all employees

• Good group discussion and participation from small groups

• Better than the same old safety stuff

• One more step upward in the improvement process

Although this is just one company case, this example shows that the content of these ARTs can

and should be more carefully considered as a part of the overall HSMS on site. Specifically, 

incorporating more “soft skills” (i.e., not engineering) about communication, leadership, and 

how to intervene when risks are identified, could be something that all mine sites, as in the above

case, are eager to learn. An example of the same company trying to incorporate some of these 

soft skills around listening and communicating is shown in Figure 15. The module within this 

workbook is situated within other modules around effective communication, teamwork, and 

leadership. Within this specific section, however, efforts were taken by the company to improve 

communication up and down the chain of command in order to more effectively achieve 

company goals. This topic speaks directly to common gaps that are heard when visiting mine 

sites and shows that targeted training efforts are possible within the mining sector.
40

Figure 15. Excerpt from CRH Oldcastle Materials Group ART [McGuire and Snead 2017].
41

Empowerment initiatives to develop an accountable workforce

Known as workers’ rights under several MSHA regulations, including the Federal Mine Safety 

and Health Act of 1977, workers have the right to refuse to work in unsafe or unhealthy 

conditions—as long as the supervisor was notified and given time to correct the risky situation 

[MSHA 2010]. OSHA also includes training about workers’ rights and encourages workers to 

initiate or request a temporary shutdown of work activities that are perceived to be unsafe 

[OSHA 2016].

This action has also been termed “empowerment training” and has been included in safety 

leadership development training and instruction in the construction industry by the Center for 

Construction Research and Training (CPWR) [2015] and may be useful for the mining industry.

For example, within their foundations for a leadership safety development guide, one of the five 

skills or actions of an effective leader is to engage and empower team members. This can be 

done by encouraging workers to identify and act upon unsafe situations by reporting hazards, 

near misses, and other safety concerns, providing solutions, and stopping work if necessary

[CPWR 2015; Schneider 2017].

Tasks discussed that leaders can do to engage and empower their workforce is to explain why 

safety is critical and engage workers in safe decision making—which was one question within 

the worker engagement section of the NIOSH survey. The CPWR training [2015] also discusses 

the importance of having pre-shift safety meetings as well as worker-manager discussions and 

walk-arounds throughout the day, also aspects that have been emphasized as a result of the 

current NIOSH survey [e.g., Haas 2019]. Finally, leadership can further empower workers to 

report site hazards or risks by developing and completing a list that shows when issues were 

raised and how they were addressed by the organization, which helps establish accountability on 

behalf of both management and the workforce [CPWR 2015; Haas and McGuire 2019]. 

Additional efforts to improve worker engagement and accountability are also discussed in a 

subsequent section of this report.

Intervening to Change Risk Tolerance 

Research suggests that individuals make risk-based decisions based on their individualized 

concept of risk [Eklöf and Törner, 2002; Huang et al., 2007; Mearns et al. 2001b; Rundmo 2001; 

Slovic et al. 2005]. Therefore, one advantage or disadvantage, depending on the individual, is 

that risk tolerance is an emergent state that can change over time [Sitkin and Weingart 1995]. As 

a result, it may behoove organizations to improve any risk assessment processes or programs that 

occur onsite.

Individual risk assessment contains three steps, as outlined by Fennell [2017]: (1) hazard 

recognition; (2) perception; and (3) decision making. In general, most operations have 

mechanisms in place for hazard identification and subsequent risk perception such as job safety 

analyses [OSHA 2002]. However, the greatest threat is rarely missing a hazard but rather, failing 

to mitigate the hazard due to a high, inaccurate tolerance for risks [Fennell 2015; Jones 2015]. 

Fennell [2015] argued that, rather than conduct training about hazard recognition and risk 

perception, more attention should be given to this third step—the decision-making process

[NIOSH 2006].
42

With the above context in mind, practitioners need to better understand what contributes to 

workers’ high levels of risk tolerance in order to build an effective risk management program 

[Jones 2015]. Fennell [2017, 2015] proposed 10 risk tolerance factors that overlap with previous 

research [e.g., Eklöf and Törner 2002; Harrell 1990; Huang et al. 2007; Mearns et al. 2001b; 

Rundmo 2001]. These factors have been adopted by several high-risk industries and, in some 

cases, are displayed at mine sites to prompt specific conversations around this issue. The 

following 10 risk tolerance factors are often addressed in additional ways with the workforce:

1. Overestimating capability or experience

2. Familiarity with the task

3. Severity of the outcome

4. Voluntary actions and being in control

5. Personal experience with an outcome

6. Cost of non-compliance

7. Confidence with the equipment or task

8. Confidence in protection and response

9. Potential profit or gain from risky actions

10. Role models accepting risk

These 10 risk tolerance factors can be addressed in additional ways with the workforce. Mainly, 

it is important for the organization and management to address these 10 factors via 

communication and support to the workforce. One method commonly used has been 

organizations utilizing employees to be advocates for messages around risk-taking and risk 

tolerance. As one example, a large aggregates company created a series of risk tolerance videos 

that featured members of its safety teams that focused on each one of these 10 factors. These 

videos are publicly available on YouTube and referenced by other companies [e.g., Callanan 

Industries 2019] in an effort to guide workers’ safe decision making when confronted with a 

risky situation as well as advocate support for taking action to quickly prevent or mitigate an 

incident if necessary. Other companies have created similar videos that, although not shown on 

YouTube, are distributed company-wide to promote workers’ assessment of risks and 

appropriate response to those risks.

Organizations do not have to undergo large social media efforts; however, being aware that this 

survey has shown that approximately 10% of a workforce is likely to engage in risky behaviors 

on a regular basis and knowing some of the contributing reasons can be helpful when trying to 

intervene. It is also important to note that workers often accept both health and safety risks to get 

their job done [Haas et al. 2019; Schneider 2017]. However, one advantage is that risk tolerance 

or avoidance are emergent traits that can change over time [Sitkin and Weingart 1995]. Because 

numerous situations combine and interact over time to define the way that risk is holistically 

evaluated for each individual worker [Reason 1997], it is particularly important for management 

to reinforce safety communication and support on site and be aware of the 10 factors that 

contribute to risk tolerance and seek to prevent a sense of complacency or pressure among the 

workforce. Follow-up results with a handful of companies did show a substantial reduction in the 

number of employees who noted regular participation in risky behaviors, showing that working 

on decision-making efforts with workers rather than recognition efforts can be useful in 

sustaining safety. This is a significant, yet unreferenced area to date, except for some narrativebased research in health behavior and injury prevention [Cole 1997].
43

Improving Engagement Efforts

Engagement, although measured as an organizational construct in the current survey, has both 

organizational and individual roots. Kahn [1990] discussed engagement being made up of 

workers’ value congruence, perceived organizational support, and core self-evaluations. 

Additionally, Ashforth and Humphrey [1995] argued that engagement accounts for both 

workers’ motivation on the job as well as their behavioral tendencies that influence safety

performance. Studies have shown that engagement significantly accounts for the relationships 

between several organizational and individual antecedents and worker performance outcomes 

[Rich et al. 2010]. For example, in Rich and colleagues’ [2010] case study research with 

firefighters, they found that those who were more engaged at work not only invested 

significantly more energy on the job but also were more helpful and involved in ways to improve 

organizational outcomes. One hypothesis could be that those who feel more engaged at work

could consider their job to have more “roles” in the organization that they affiliate with in 

addition to just their specific job-related tasks. In turn, they may contribute to more efforts and 

initiatives at work.

Although engagement as a construct in the current research effort scored as one of the lowest 

perceived organizational factors, it is important to note that engagement is made up of quickly 

changing moments and occurs in more of an ebb and flow [Kahn 1990]. For example, if recent 

initiatives occur on site that involve workers in some type of decision-making activity that 

positively affects them, it is likely that scores would be higher. Below is a list of examples that 

were discussed as employee-involvement initiatives that seemed to “work” in terms of being 

recognized by employees.

• Letting employees choose a new type of personal protective equipment (PPE) based on a 

variety of approved options. Examples of this sort of collaborative effort have been done 

previously, such as knee pad design research with NIOSH, MSHA, and participating 

mine companies. For examples of these sorts of collaborations on a research level, refer 

to Moore et al. 2011 and Moore et al. 2008. However, the current research has shown that 

maintaining daily activities and decision point in which everyone can be involved is 

critical to workers feeling involved in worksite processes.

• Creating and involving employees on different health and safety committees, including 

participation in walk-throughs and debriefs on site. Additionally, targeting specific 

groups who appear to have lower perceptions or perceived morale on site (e.g., specific 

age group, experience group) has demonstrated success.

• Improving, through documentation and management by walking around and

communication quantity and quality throughout the workday.

These examples pick up on an important distinction between training the workforce and 

involving the workforce. Although training the mining community is critical, a more futuristic 

option, as discussed by Kohler [2015], is that, in comparison to traditional training, workers 

“should be empowered with knowledge, skills, and abilities, rather than ‘trained,’ to recognize 

and mitigate hazards” [p. 331]. Kohler [2015] goes on to discuss HSMS as a powerful 

framework to ensure worker and manager accountability in the successful implementation and 

measurement of health and safety efforts.
44

The challenge among the current sample was finding activities in which first, workers would 

readily participate and second, that they would perceive as activities in which their efforts were 

valued and used to improve health and safety initiatives. Research has shown that in order to 

foster value congruence for site safety, positive and consistent leadership is needed along with 

consistent opportunities for developed, shared perceptions of safety [Schwatka et al. 2016]. 

Within the current safety climate study, several mine sites noted that they have suggestion boxes, 

open door policies, or safety committees in which all opinions are considered and valued. 

However, as other worker participation efforts have shown in the construction industry, workers 

may be reluctant to give health and safety input at first due to a historic culture of blame 

[Schneider 2017].

As illustrated in the above intervention examples, finding ways for workers to participate in daily 

decisions on the job is critical to improving perceptions and workplace norms, ultimately 

affecting worker H&S performance. Schneider [2017], through the American Industrial Hygiene 

Association, offered several examples of how construction workers can participate in jobsite 

safety. Many of these examples are applicable to the mining industry such as workers 

participating in safety orientation sessions to learn how they can be involved in safety and even 

present aspects of the site orientation; help develop and present toolbox talks; help train or task 

train workers in hazard recognition and mitigation; be trained in and conduct safety audits on 

site; participate in worksite safety inspections and incident investigations; and be part of problem 

solving and planning teams in any health or safety area being addressed on site (paraphrased 

from p. 8).

Finally, by participating in NIOSH’s safety climate surveys, companies were able to better 

determine which groups, if any, had more negative perceptions of safety and support on site. 

This allowed organizations and management to better target and involve certain groups of 

workers in future interventions. At one underground coal mine, for example, the group of 

workers who were between 35 and 44 with 11–20 years of experience had the lowest perceptions 

of safety climate in almost all areas of the survey measured. So, the company made specific 

efforts to further engage with this subgroup of employees and solicit involvement in the safety 

committee on site. In follow-up assessments, although their perceptions were still lower than 

other subgroups on site, their perceptions of management support and communication had 

improved.

Maintaining Thoroughness and Improving Sense of Control 

The safety climate results showed that personal factors have a larger impact on worker H&S 

performance than those external factors measured in the survey. Therefore, being aware of how 

any changes to the HSMS processes or policies may impact aspects such as workers’ 

thoroughness and perceived sense of control, is important. Specifically, the sense of control 

construct often received a low score across mine sites. Research has shown that individuals who 

have a higher, internal locus of control can more objectively deal with situations that occur on 

the job, have a better perception of their work environment, and are more motivated on the job 

[Erez and Judge 2001]. More specifically, workers with a higher internal locus of control have 

demonstrated better social skills [Ringer and Boss 2000] as well as more proactive qualities, and 

they tend to engage in problem-focused activities such as mitigating a hazard [Gianakos 2002; 

Ng and Butts 2009; Ng et al. 2006].
45

Although these are personal factors, these states can be influenced by organizational 

characteristics such as decision-making authority bestowed onto an individual (e.g., giving 

workers “stop work” authority if necessary), opportunities provided to use knowledge and skills, 

the option and ability to participate in site-wide initiatives [Karasek and Theorell 1990], and 

rewarding such decisions and actions that result in a safer workplace. It can be suggested, then, 

that the root cause, and perhaps a potential longer-lasting solution of organizational conflicts 

regarding workplace safety, may reside in understanding the processes undertaken by

organizations to communicate with individuals. Specifically, short-term interventions and 

communication efforts can prompt changes to work practices but seldom maintain them [Mullan 

et al. 2015]. Rather, management and organizations determining ways to communicate with their 

workforce in ways that help appease or further develop intrinsic motivations rather than extrinsic 

motivations, has been deemed highly effective in high-risk industries [Laitinen and Päivärinta 

2010; Lingard and Rowlinson 1997]. As an example, determining if a safety initiative is not 

endorsed as it should be can be useful in determining a misaligned communication between 

managers and hourly workers. In other instances, supervisors being visible on site and engaging 

in positive monitoring and feedback on the job have been shown to be effective in enhancing 

worker perceptions and behavior [Mullan et al. 2015]. Through greater understanding, 

communication, and involvement, practitioners can continually determine new ways to facilitate 

alignment between management and hourly workers. 

Accountable Communication through Performance Assessments

Safety communication has been continuously encouraged in high-risk industries as an effective 

mechanism to enhance workers’ awareness of safety and appropriate response to risks [Clarke 

2003; Griffin and Neal 2000; Mearns et al. 2003; Probst 2004]. HSMS programs, such as the 

CoreSafety Program developed by the National Mining Association (NMA), includes 

responsibility, accountability, communication, and collaboration as core elements [NMA 2014]. 

A common theme within several of the CoreSafety Program modules that detail specific 

elements are to “Lead by Example,” and indicates that management must ensure that workers 

understand their roles and responsibilities, provide resources to fulfill those responsibilities, and 

use appropriate tools to measure and review for continuous improvement.

Communication that works well has been shown to contribute to financial gains of a company 

and can also enhance the organization’s reputation [Kaplan and Norton 2004]. A specific gap

identified in the current research is the lack of accountable communication between managers 

and workers in the workplace [Haas 2019]. This gap was likely identified because there is little 

research being done in this area [Van Ruler 2000; Fleisher and Mahaffy 1997]. Historically, it 

has been difficult to identify a relationship between communication efforts and results. However, 

HSMS intervention research has been able to show gaps and best practices [Haas 2019; Haas et 

al. 2018b; Haas et al. 2016; Haas and Yorio 2016] and that there is room for improvement. In 

response, NIOSH developed communication accountability scorecards to help organizations 

make communication management more transparent in a way that conforms to ideas behind 

organizational policies, practices, and processes within most HSMSs (Appendices J, K, L).

These communication scorecards were developed using previous research about performance 

measurement in HSMS [Haas and Yorio 2016] as well as results gleaned about communication 

indicators and measurement. Specifically, results from these safety climate surveys as well as 
46

qualitative data collected from managers and workers about communication practices on site 

[e.g., see Haas 2019] informed the quality indicators identified. These scorecards were piloted 

with eight members of H&S management from three companies to ensure that the objectives, 

measures, and indicators were accurate ways to assess communication quantity and quality. 

These communication cards were pilot-tested with eight H&S managers from three mine 

companies. The pilot companies were able to verify that the intervention measures listed were 

common and that the communication quality indicators aligned with their overall HSMS 

implementation goals. Additionally, they were able to provide feedback about ways in which 

they could adapt and use these communication scorecards daily to assess and measure messages 

that were being exchanged on site about health and safety. Using such a tool also helps make 

communication as a management effort more tangible.

After minor tweaks were made for consistency, three cards aim to improve critical gaps 

identified between managers and hourly workers (i.e., visibility, consistency, and fairness) [Haas 

2019]. The final scorecards (Appendices J, K, and L) were developed in response to the current 

research efforts to help improve communication and, consequently, the perceived safety climate. 

Similar gaps such as clarity, effectiveness, responsiveness, and consistency have been identified 

in research on other industries [Vos and Schoemaker 2004]. Additionally, others have touted 

such communication scorecards as an “ideal communication method” [Olve et al. 2003, p. 199],

making this method a viable approach to assess and improve aspects of accountable 

communication. In response to these tools focusing on communication assessment, companies 

are able to adapt these cards to be more specific to a health or safety issue being addressed on 

site to ensure communication in this area. For example, one company has taken these cards and 

created a set for workers and set for managers that was integrated into a powered haulage 

management plan [Haas and McGuire 2019; McGuire et al. 2019]. They labeled these cards 

“Plan to Eliminate and Manage Powered Haulage Accidents, Injuries and Fatalities” and 

included performance indicators around barriers to mobile haulage safety (e.g., inadequate 

berms, using conveyors to move materials, visibility out of large vehicles, etc.), which then 

included communication indicators for workers and managers to discuss and mitigate.

Conclusion

This study contributes valuable knowledge to the mining sector. Considering that meta-analytic 

studies have found that the effect size of safety climate exceeds that of hazards and other 

unknown risks [Nahrgang et al. 2011], understanding sector, subsector, and site-specific trends in 

safety climate constructs is critical to managing H&S performance. Besides establishing current 

benchmarks of safety climate in the mining industry, these results show the impact that 

organizational and personal safety climate factors can have on safety performance. Because other 

studies have already conveyed the significant, positive relationship between safety climate and 

safety performance [e.g., Guldenmund 2000; Wiegmann et al. 2002; Smith and DeJoy 2014; 

Zohar 1980], it was important for NIOSH to further characterize the impact of these indicators to 

provide support to mine organizations in tailoring their HSMS implementation efforts.

This report addressed aspects of both organizational and personal factors that play a significant 

role in worker perceptions and performance. The analysis rendered several statistically 

significant results and accounted for a large proportion of variance (approximately 50%) in
47

workers’ performance. Although a large R

2

value was determined, it is also worth mentioning 

that future research should assess where the other 50% can be accounted for to help prevent 

future incidents. It is possible that some of the unaccounted variance can be attributed to random 

error or short-term motivating factors that come and go both on behalf of the organization and 

the workforce.

Additionally, it remains important that companies continually assess their safety climate to 

establish benchmarks that provide a more holistic view of the overall culture. Several 

participating companies did request follow-up assessments after significant changes to company 

programs and processes were made. For example, one company participated in this effort in 

February 2016 and again in February 2017 to find that worker perceptions had significantly 

improved, especially in areas related to risk tolerance, communication, and perceived support 

[Haas et al. 2017]. However, future research should build in the time and capacity for formal 

longitudinal assessments to establish HSMS indicators that are effective in improving the safety 

culture at mine sites. Along these lines, it is possible that more collaboration with MSHA’s 

technical support division can be used to obtain and maintain worker involvement in mine 

organization’s safety culture efforts.

Eventually, it is possible that more short-term constructs can be accounted for and measured to 

better understand what factors are likely to come and go more quickly than others and could 

account for H&S incidents. In the meantime, this report provides some guidance for mine 

organizations to use to improve organizational factors to help enhance the overall culture while 

supporting workers’ personal factors. It is believed that organizations can start to address a select 

number of HSMS practices and, over time, scale their system to include additional indicators.

Acknowledgements

NIOSH wishes to thank all the participating companies, individual mine sites, managers who 

coordinated visits, and all of the individual workers who participated in this research effort.
48

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Appendix A: Safety Climate Antecedents in Worker Performance

A lengthy literature review of safety climate, safety culture, and organizational values in highrisk occupations rendered a list of organizational and personal antecedents to workers’ 

performance (hereafter referred to as worker proactivity and worker compliance) on the job. 

Regarding the organizational antecedents to worker performance, the following were identified: 

supervisor support; supervisor communication; organizational H&S support; adequacy of safety 

training; employee involvement/engagement; and coworker communication. Important distal, 

person-related factors identified in the literature search included adaptability, sense of control, 

thoroughness, and risk tolerance. A review of these antecedents and the development or adoption 

of scales to measure their presence in the mining industry is discussed below.

Organizational Predictors of Worker Performance

Much research including meta-analyses has identified organizational elements that support a 

strong safety climate and predict worker performance [see Brondino et al. 2012; Flin et al. 2000; 

Griffin and Curcuruto 2016; Nahrgang et al. 2011; Neal et al. 2000].

Organizational Support: Survey items 23–25

This scale measures the degree of priority assigned to safety within the organization. Priority of 

safety refers to employee expectations and daily behaviors regarding the balance maintained 

among work pace, workload, and pressure for productivity and safety [Zohar 2000]. This 

positive reinforcement of safety behavior often entails supporting work at a slower pace and

investing in extra resources, including staff and equipment. The priority of safety in the 

organization has been the subject of many research investigations (including numerous metaanalyses) and has consistently been found to be a strong predictor of worker safety knowledge, 

motivation, and behavior (see the meta-analyses conducted by Clarke 2006 and Christian et al. 

2009). The construct has also been found to moderate the relationship between health and safety 

management systems and safety performance [Naveh et al. 2011] as well as leadership and safety 

performance [Hofmann et al. 2003].

Coworker Communication: Survey items 26–28

Communication with coworkers and trust in coworkers imply that coworkers will accept 

mistakes as learning experiences, which is more likely to encourage individuals to try things 

beyond core tasks and enhance their own self-efficacy. If individuals have trust in coworkers’ 

abilities and believe other coworkers will support them, then they are likely to feel more open to 

change and to feel in control. Also, if individuals believe that their relationship with coworkers is 

characterized by trust, they are likely to gain confidence in their own abilities. This also 

promotes sharing of safety ideas and physical cooperation and has been empirically shown to 

enhance occupational safety/lower injury rates [Zacharatos et al. 2005]. The importance of 

horizontal communications and coworker trust has steadily risen to the forefront of interest 

among organizational safety scholars [see Conchie et al. 2006; Burt et al. 2009].
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Supervisor Support: Survey items 29–31

Supervisors act as agents of the organization who have responsibility for directing and evaluating 

worker performance. Workers often view their supervisor’s favorable or unfavorable orientation 

toward them as indicative of the organization’s posture toward them. Supervisor support captures 

a worker’s perception regarding the degree to which supervisors value his or her contribution to 

the organization and care about the individual’s personal well-being. Parker et al. [2006] 

empirically tested and found that supervisory support has been shown to stimulate proactive 

behaviors. This construct has been found to be a strong predictor of important organizational and 

worker-related outcomes [Eisenberger et al. 2002; Kottke and Sharafinski 1998; Rhoades et al. 

2001], including safety- and health-related outcomes [Cousins et al. 2004].

Supervisor Communication: Survey items 32–38

Supervisors who care about safe work and the health and safety of their workers should 

emphasize safe work among their employees. One way for supervisors to emphasize and foster 

safety and health behaviors is to monitor worker behaviors and provide feedback when their 

behaviors are unsafe or do not conform to company safety procedures [Zohar 2002; Zohar and 

Luria 2003; Luria et al. 2008]. Tyler and Blader [2005] developed and tested a construct that 

succinctly measures workers’ perceptions of their immediate supervisors monitoring and 

detection of behaviors in an occupational setting. This construct is designed to assess employee 

expectations about the likelihood of their behavior being detected and their judgments about 

expectancies of behavior being observed. Detection of behavior has also been found to be an

important predictor of whether employees report following organizational rules. Finally, vertical 

safety communication has been established as a significant predictor of employee safety 

behaviors and workplace injuries [e.g., Hofmann and Stetzer 1998; Michael et al. 2006; 

Cigularov et al. 2010; Zacharatos et al. 2005]. This construct captures both downward sharing of 

safety information (related to specific workplace hazards and safety procedures) as well as the 

ease with which workers can communicate with their supervisors and managers about workplace 

H&S issues.

Worker Involvement/Engagement: Survey items 39–42

This construct reflects workers’ perceptions that the organization is willing to involve them in 

decision-making processes about the procedures that influence their work. This is consistent with 

the construct of procedural justice commonly researched in the organizational and industrial 

psychology literatures. If employees perceive the outcomes of their evaluations to be fair or 

perceive the process by which outcome allocation decisions are made to be fair, they will be 

more likely to reciprocate by performing behaviors to benefit the organization that go beyond the 

in-role performance of their jobs. Employee involvement, as well as the related procedural 

justice construct, has been found to be a predictor of safety-related outcomes [Hystad et al. 2014; 

Carmeli et al. 2010].

Perception of Adequate Safety Training: Survey items 49–51

Zacharatos and colleagues [2005] noted that occupational safety training is heavily researched 

and that most studies suggest that workers who receive safety training are less likely to get 

injured than those who have not been trained. In general, safety training is designed to increase

worker knowledge and awareness of hazards and risks and the types of behaviors needed to 

avoid injury and illness in general and specific contexts. Evans and Davis [2005] noted that the 
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benefits of training go beyond safety knowledge and awareness when they suggested that as 

worker behavior becomes more reliably safe through effective safety training, trust among the 

collective workforce is also enhanced. This, in turn, can lead to increased cooperation and 

information sharing around safety issues and lead to an overall decrease in safety incidents.

Personal Predictors of Performance

Sense of Control: Survey items 10–13

Locus of control represents the extent to which people believe that the rewards they receive in 

life can be controlled by their own personal actions [Lefcourt 1976; Rotter 1966]. A metaanalysis by Ng and colleagues [2006] provides a recent review of research examining the role of 

locus of control in the workplace. Work locus of control represents the extent to which people 

attribute rewards at work to their own behavior (example work locus of control items include 

“People who perform their jobs well generally get rewarded” and “Most people are capable of 

doing their jobs well if they make the effort” [Spector 1988]). Locus of control often is a 

significant predictor of job stress as well. The locus of control construct was adapted from 

previous constructs that measured core self-evaluations [Judge et al. 2003; Parker et al. 2006].

Thoroughness: Survey items 14–18

An individual who is conscientious is orderly, dependable, and responsible. The 

conscientiousness factor is one of the “big five” personality traits and has appeared under the 

names dependability, task interest, will to achieve, impulse control, and work. Other facets used 

to describe this variable include competence, order, dutifulness, achievement striving, selfdiscipline, and deliberation. Conscientiousness is used in the current study because research has 

shown that this is the personality trait with the most predictive utility [e.g., Barrick and Mount 

1991; Bogg and Roberts 2004; Poropat 2009].

Risk Tolerance/Avoidance: Survey items 19–22

The risk propensity scale was developed to measure an individual’s general tendency to take 

risks [Weigold and Schlenker 1991; Meertens and Lion 2008]. An individual’s level of risk 

propensity may determine the types of health and safety behaviors they are willing to engage in 

high-risk occupations and risky situations [Hatfield and Fernandes 2009]. Measuring risk 

avoidance can help predict the types of at-risk behaviors in which workers are willing to 

participate [Hatfield and Fernandes 2009]. Thus, a risk avoidance scale was adapted and used to 

measure an individual’s general tendency to take risks and general avoidance of risks on site 

[Weigold and Schlenker 1991; Meertens and Lion 2008). A scale was adapted from the Meertens 

and Lion [2008] risk propensity scale.

Adaptability: Survey items 52–54

Given that the proactive safety behaviors involve changing the work environment, individuals 

with an active orientation toward change may be more prone to behave proactively in the 

workplace. An active-change orientation is similar to “felt responsibility for change,” or “an 

individual’s belief that he or she is personally obligated to bring about constructive change” 

[Morrison and Phelps 1999, p. 407]. Morrison and Phelps argued that those with high felt 

responsibility for change will perceive taking charge positively because it provides a sense of 

personal satisfaction and accomplishment. Both active-change orientation and felt responsibility 
62

for change have been shown to predict proactive behavior [Frese and Pluddemann 1993]. Parker 

and colleagues [2006] indeed found that individuals with a strong adaptability and change 

orientation are more likely to engage in proactive behaviors at work.
63

Appendix B: NIOSH Safety Climate Survey
64

Figure 16. NIOSH safety climate survey cover sheet.
65

Figure 17. Page 1 of the NIOSH safety climate survey with questions assessing perceived 

proactivity, compliance, sense of control, thoroughness, and risk tolerance.
66

Figure 18. Page 2 of the NIOSH safety climate survey with questions assessing perceived 

organizational support for H&S, coworker communication, supervisor support for H&S, 

supervisor communication, and worker engagement.
67

Figure 19. Page 3 of the NIOSH safety climate survey with questions assessing perceived 

H&S knowledge, H&S motivation, H&S training adequacy, worker adaptability, and 

frequency of near misses and incidents experienced in the last 6 months.
68

Figure 20. Demographic page of the NIOSH safety climate survey.
69

Appendix C: Overall Benchmarking Results/Averages
70

Table 14. Results for proactivity items overall for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

go out of my way to address 

potential hazards 0.9 1.9 5.7 15.6 34.4 41.4 5.05

voluntarily carry out tasks that 

help improve H&S 0.7 1.3 5.0 16.8 40.1 36.1 5.03

make suggestions to improve 

how H&S is handled 1.1 3.0 8.6 22.4 37.0 27.8 4.75

try new things to improve 

workplace H&S 1.4 2.7 9.3 23.5 36.4 26.7 4.71

try to solve problems in ways 

that reduce H&S risks 0.8 1.4 4.8 16.5 39.2 37.3 5.04

Table 15. Results for compliance items overall for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average

don’t take risks that could 

result in an accident 1.1 1.5 4.5 10.4 25.7 56.8 5.28

use all necessary H&S 

equipment to do my job 0.7 1.0 3.6 10.7 30.5 53.5 5.30

use the correct H&S 

procedures for carrying out my 

job

0.6 0.5 3.1 10.7 34.1 50.9 5.30

always report all H&S-related 

incidents 1.1 1.8 6.4 12.9 26.9 50.9 5.15
71

Table 16. Sense of control overall for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

I can pretty much achieve 

whatever I set out to do 0.9 0.7 4.0 14.6 41.7 38.0 5.10

I can do something if I am 

unhappy about a decision 4.7 5.3 10.6 24.1 35.2 20.1 4.40

I can stay healthy/safe if I take 

the right actions 0.8 0.7 1.6 7.4 32.2 57.2 5.41

most problems that I 

experience are “out of my 

hands”

13.7 20.2 19.5 20.3 16.2 10.1 3.65

Table 17. Thoroughness overall for each response option (%) and item average (on a 6-point scale)

When doing my job...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

I am always thorough 0.6 1.5 5.5 23.4 45.0 23.9 4.82

I can be somewhat careless 

with my work tasks 42.8 29.5 10.4 7.7 6.3 3.3 4.85

I'm a reliable worker 1.2 0.1 0.5 2.1 26.6 69.5 5.61

I work until my task is finished 0.7 0.7 1.2 8.2 34.7 54.5 5.39

I know when to seek help 

during a difficult task 0.8 0.9 2.6 7.8 34.8 53.1 5.34
72

Table 18. Risk tolerance overall for each response option (%) and item average (on a 6-point scale)

As far as day to day work...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

I do not take risks with my 

safety/health 1.4 1.9 4.6 11.2 30.1 50.7 5.19

I take risks regularly 51.6 27.8 8.6 4.8 4.0 3.1 5.09

safety comes first 1.0 0.6 2.2 6.0 23.4 66.9 5.51

I prefer to avoid risks 2.0 1.5 2.7 6.9 27.0 59.9 5.35

Table 19. Organizational support for H&S overall for each response option (%) and item average (on a 6-point scale)

As far as day to day work...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

H&S rules and procedures are 

sometimes ignored 26.0 23.1 13.6 17.9 13.6 5.8 4.13

it doesn’t matter how the work 

is done if there are no accidents 47.9 24.5 9.5 7.4 5.9 4.7 4.87

I often have impossible 

production pressures

21.6 23.6 18.2 19.1 11.8 5.7 4.07
73

Table 20. Coworker communication overall for each response option (%) and item average (on a 6-point scale)

Everyone in my crew...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

has confidence in each other to 

work safely 1.6 2.4 5.9 15.0 39.0 36.0 4.95

helps each other with H&S 

problems at work 0.9 2.0 4.6 14.2 42.2 36.1 5.03

informs each other about 

potential workplace H&S 

hazards

0.8 1.4 4.1 12.0 37.8 43.9 5.16

Table 21. Supervisor support overall for each response option (%) and item average (on a 6-point scale)

My supervisors...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

try to help me do my job as 

safely as possible 1.7 2.9 4.9 13.0 31.9 45.6 5.07

help me if I have a H&S 

problem at work 1.5 2.3 5.3 11.9 35.9 43.2 5.08

don’t notice if I do my job 

safely 32.9 27.2 11.4 11.4 10.7 6.4 4.41
74

Table 22. Supervisor communication overall for each response option (%) and item average (on a 6-point scale)

My supervisors...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

remind me to follow H&S 

work rules 1.9 3.2 6.0 14.2 37.5 37.4 4.94

closely monitor my H&S work 

practices 3.3 6.1 12.3 24.3 32.7 21.2 4.41

take action if I don’t follow 

H&S work practices 2.4 3.6 7.6 17.2 37.1 32.2 4.80

clearly explain H&S rules to 

me

2.2 3.8 7.9 15.9 35.8 34.5 4.83

regularly inform me of work 

hazards specific to my job 3.4 5.4 9.8 18.8 31.9 30.7 4.63

encourage communication 

about H&S problems 2.8 3.3 7.4 15.6 33.4 37.4 4.86

I am satisfied with my 

supervisor’s H&S management 4.5 4.1 6.2 13.6 32.5 39.1 4.83
75

Table 23. Worker engagement overall for each response option (%) and item average (on a 6-point scale)

When it comes to the H&S 

rules...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

the same rules apply to all 

employees 6.6 4.6 6.2 9.6 24.8 48.3 4.86

I can question the 

rules/procedures that influence 

my work

5.0 6.5 7.5 15.8 33.0 32.2 4.62

concerns are heard before 

making new rules or 

procedures

6.0 6.9 10.5 19.2 31.4 26.0 4.41

I am involved in improving 

H&S rules and procedures 6.2 8.9 13.6 21.9 27.4 22.0 4.21

Table 24. H&S knowledge overall for each response option (%) and item average (on a 6-point scale)

I know how to...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

use H&S equipment to follow 

standard work procedures 0.3 0.4 2.3 8.9 38.3 49.7 5.34

maintain or improve workplace 

H&S 0.5 0.9 2.9 12.1 41.8 41.8 5.19

reduce the risk of workplace 

H&S incidents at my job 0.4 0.9 2.4 11.4 40.1 44.8 5.24
76

Table 25. H&S motivation overall for each response option (%) and item average (on a 6-point scale)

It is important to...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

maintain workplace health and 

safety at all times 0.4 0.3 1.1 4.3 22.2 71.8 5.63

reduce the risk of workplace 

H&S incidents at my job 0.4 0.3 0.9 4.7 22.3 71.4 5.62

maintain or improve my 

personal H&S 0.5 0.3 0.9 4.3 21.4 72.5 5.63

Table 26. H&S training adequacy overall for each response option (%) and item average (on a 6-point scale)

When it comes to H&S 

training...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

this site provides enough 

training for me to do my job 1.6 2.2 4.6 11.4 34.4 45.7 5.12

it helps me do my job as 

healthy/safely as I can 1.0 1.6 3.7 10.7 36.5 46.4 5.19

it is not a priority here 61.2 18.2 5.7 6.0 5.1 3.7 5.13
77

Table 27. Adaptability overall for each response option (%) and item average (on a 6-point scale)

In general I think that...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

tried and tested ways of doing 

things are usually the best 3.0 5.4 11.3 25.0 33.7 21.5 4.45

I can handle any changes that 

come along 0.7 1.1 4.6 17.6 46.1 29.9 4.97

changes in my work routine 

keep my job interesting 3.3 4.1 8.6 19.6 37.9 26.4 4.64
78

Appendix D: Overall Results/Averages for the Coal Industry (n = 358)
79

Table 28. Proactivity in coal for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

go out of my way to address 

potential hazards

2.0 1.7 4.5 16.5 38.3 37.2 4.99

voluntarily carry out tasks that 

help improve H&S

0.6 1.1 5.3 19.3 41.9 31.8 4.96

make suggestions to improve 

how H&S is handled

1.1 4.8 10.7 25.3 34.0 24.2 4.59

try new things to improve 

workplace H&S

0.8 2.8 8.7 25.8 38.9 23.0 4.68

try to solve problems in ways 

that reduce H&S risks

0.8 1.4 4.2 16.8 39.9 36.9 5.04

Table 29. Compliance in coal for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

don’t take risks that could 

result in an accident

1.4 2.0 6.7 12.6 29.7 47.6 5.10

use all necessary H&S 

equipment to do my job

1.1 1.7 9.2 14.8 33.8 39.4 4.97

use the correct H&S 

procedures for carrying out my 

job

1.1 0.6 5.0 17.3 37.4 38.5 5.05

always report all H&S-related 

incidents

1.7 2.5 15.5 20.6 26.5 33.2 4.67
80

Table 30. Sense of control in coal for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

I can pretty much achieve 

whatever I set out to do

0.6 1.4 3.9 16.8 41.2 36.1 5.05

I can do something if I am 

unhappy about a decision

5.3 5.0 16.2 25.5 30.8 17.1 4.23

I can stay healthy/safe if I take 

the right actions

0.8 1.1 2.2 10.4 34.5 51.0 5.29

most problems that I 

experience are “out of my 

hands”

10.5 21.8 24.9 20.9 15.8 6.2 3.71

Table 31. Thoroughness in coal for each response option (%) and item average (on a 6-point scale)

When doing my job...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

I am always thorough 0.3 3.1 6.4 24.6 46.6 19.0 4.71

I can be somewhat careless 

with my work tasks

35.8 35.5 10.6 8.9 7.0 2.2 4.77

I'm a reliable worker 1.7 0.0 0.0 3.1 31.6 63.7 5.54

I work until my task is finished 0.3 0.6 2.2 9.2 35.6 52.1 5.36

I know when to seek help 

during a difficult task

0.8 2.5 4.5 9.5 37.7 45.0 5.16
81

Table 32. Risk tolerance in coal for each response option (%) and item average (on a 6-point scale)

As far as day to day work...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

I do not take risks with my 

safety/health

0.3 3.1 8.7 19.7 32.3 36.0 4.88

I take risks regularly 38.6 32.7 11.8 7.6 7.0 2.3 4.81

safety comes first 1.7 0.8 2.5 7.9 27.0 60.1 5.38

I prefer to avoid risks 2.2 2.5 3.6 9.2 31.4 51.0 5.18

Table 33. Organizational support for H&S in coal for each response option (%) and item average (on a 6-point scale)

As far as day to day work...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

H&S rules and procedures are 

sometimes ignored

15.5 20.9 18.9 22.6 15.5 6.5 3.79

it doesn’t matter how the work 

is done if there are no accidents

28.9 28.6 17.3 14.2 6.2 4.8 4.45

I often have impossible 

production pressures

16.3 23.8 19.8 19.2 14.3 6.6 3.89
82

Table 34. Coworker communication in coal for each response option (%) and item average (on a 6-point scale)

Everyone in my crew...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

has confidence in each other to 

work safely

1.7 2.5 6.8 17.2 40.0 31.8 4.87

helps each other with H&S 

problems at work

0.8 2.8 6.8 16.4 44.5 28.6 4.87

informs each other about 

potential workplace H&S 

hazards

0.8 2.8 7.1 12.4 39.8 37.0 4.99

Table 35. Supervisor support in coal for each response option (%) and item average (on a 6-point scale)

My supervisors...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average

try to help me do my job as 

safely as possible

0.6 3.9 5.9 14.4 32.1 43.1 5.03

help me if I have a H&S 

problem at work

0.6 3.1 6.5 13.9 35.1 40.8 5.02

don’t notice if I do my job 

safely

30.3 28.6 10.2 12.5 13.3 5.1 4.35
83

Table 36. Supervisor communication in coal for each response option (%) and item average (on a 6-point scale)

My supervisors...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average

remind me to follow H&S 

work rules

1.4 5.1 8.5 19.5 35.6 29.9 4.73

closely monitor my H&S work 

practices

2.8 7.1 19.0 22.9 31.4 16.7 4.23

take action if I don’t follow 

H&S work practices

2.0 7.3 11.9 21.8 31.6 25.4 4.50

clearly explain H&S rules to 

me

2.5 5.9 10.7 20.6 30.5 29.7 4.60

regularly inform me of work 

hazards specific to my job

2.3 7.7 9.4 19.7 33.3 27.6 4.57

encourage communication 

about H&S problems

2.8 5.1 8.8 17.8 34.3 31.2 4.69

I am satisfied with my 

supervisor’s H&S management 

5.1 5.1 8.2 14.1 30.1 37.5 4.72
84

Table 37. Worker engagement in coal for each response option (%) and item average (on a 6-point scale)

When it comes to the H&S 

rules...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

the same rules apply to all 

employees

9.0 7.0 8.7 8.5 26.2 40.6 4.57

I can question the 

rules/procedures that influence 

my work

6.8 12.2 10.8 17.3 30.6 22.4 4.20

concerns are heard before 

making new rules or 

procedures

7.6 12.4 13.2 19.4 29.6 17.7 4.04

I am involved in improving 

H&S rules and procedures

8.2 13.8 17.5 22.9 23.2 14.4 3.82

Table 38. H&S knowledge in coal for each response option (%) and item average (on a 6-point scale)

I know how to...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

use H&S equipment to follow 

standard work procedures

0.3 0.6 2.0 17.4 45.1 34.6 5.10

maintain or improve workplace 

H&S

0.8 2.0 4.6 16.6 45.3 30.7 4.95

reduce the risk of workplace 

H&S incidents at my job

1.2 1.2 2.9 13.5 45.8 35.4 5.08
85

Table 39. H&S motivation in coal for each response option (%) and item average (on a 6-point scale)

It is important to...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average

maintain workplace health and 

safety at all times

0.3 0.3 0.3 6.3 28.0 64.9 5.56

reduce the risk of workplace 

H&S incidents at my job

0.6 0.6 0.6 7.4 25.1 65.7 5.53

maintain or improve my 

personal H&S

0.6 0.6 0.9 5.7 26.6 65.6 5.54

Table 40. H&S training adequacy in coal for each response option (%) and item average (on a 6-point scale)

When it comes to H&S 

training...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

this site provides enough 

training for me to do my job

2.3 4.3 5.4 16.0 35.6 36.5 4.88

it helps me do my job as 

healthy/safely as I can

1.7 2.3 5.1 16.5 37.0 37.3 4.97

it is not a priority here 53.6 22.9 8.3 7.7 2.9 4.6 5.03
86

Table 41. Adaptability in coal for each response option (%) and item average (on a 6-point scale)

In general I think that...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

tried and tested ways of doing 

things are usually the best

2.0 5.1 11.4 21.4 41.6 18.5 4.51

I can handle any changes that 

come along

0.9 1.1 7.1 23.1 42.5 25.4 4.81

changes in my work routine 

keep my job interesting

3.7 5.4 11.4 17.1 34.9 27.4 4.56
87

Appendix E: Overall Results/Averages for

Stone, Sand, and Gravel Industry (n = 1,418)
88

Table 42. Proactivity in SSG for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

go out of my way to address 

potential hazards

0.6 2.3 5.7 13.3 33.9 44.2 5.10

voluntarily carry out tasks that 

help improve H&S

0.7 1.4 5.0 14.6 40.6 37.6 5.06

make suggestions to improve 

how H&S is handled

1.2 2.7 7.0 20.3 38.0 30.8 4.84

try new things to improve 

workplace H&S

1.6 2.7 8.4 21.1 37.7 28.6 4.76

try to solve problems in ways 

that reduce H&S risks

0.7 1.3 3.8 14.8 41.0 38.4 5.09

Table 43. Compliance in SSG for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average

don’t take risks that could 

result in an accident

1.3 1.3 4.1 9.7 24.3 59.1 5.32

use all necessary H&S 

equipment to do my job

0.5 0.6 2.8 9.1 30.9 56.0 5.37

use the correct H&S 

procedures for carrying out my 

job

0.4 0.4 2.6 9.7 34.7 52.1 5.34

always report all H&S-related 

incidents

0.9 2.1 5.0 12.1 27.7 52.1 5.20
89

Table 44. Sense of control in SSG for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

I can pretty much achieve 

whatever I set out to do

0.8 0.7 4.0 14.8 42.3 37.4 5.09

I can do something if I am 

unhappy about a decision

4.6 6.0 9.8 24.8 35.2 19.7 4.39

I can stay healthy/safe if I take 

the right actions

0.7 0.6 1.4 6.9 32.4 58.0 5.44

most problems that I 

experience are “out of my 

hands”

14.3 19.3 18.6 19.6 17.1 11.0 3.61

Table 45. Thoroughness in SSG for each response option (%) and item average (on a 6-point scale)

When doing my job...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

I am always thorough 0.4 1.1 5.1 22.4 44.5 26.6 4.90

I can be somewhat careless 

with my work tasks

45.9 27.7 10.1 6.5 5.9 4.0 4.89

I'm a reliable worker 1.0 0.1 0.4 1.6 26.1 70.7 5.64

I work until my task is finished 0.7 0.6 1.0 7.5 35.4 54.7 5.40

I know when to seek help 

during a difficult task

0.8 0.6 2.1 7.6 35.3 53.7 5.37
90

Table 46. Risk tolerance in SSG for each response option (%) and item average (on a 6-point scale)

As far as day to day work...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average

I do not take risks with my 

safety/health

1.1 1.8 4.2 9.0 29.8 54.1 5.27

I take risks regularly 53.2 26.7 8.7 4.5 3.6 3.4 5.11

safety comes first 0.8 0.6 2.3 5.2 21.8 69.3 5.55

I prefer to avoid risks 2.3 1.3 3.0 5.4 25.2 62.7 5.38

Table 47. Organizational support for H&S in SSG for each response option (%) and item average (on a 6-point scale)

As far as day to day work...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average

H&S rules and procedures are 

sometimes ignored

25.9 22.5 13.3 18.1 14.1 6.0 4.10

it doesn’t matter how the work 

is done if there are no accidents

48.6 23.8 8.8 7.0 6.9 4.9 4.86

I often have impossible 

production pressures

20.4 22.1 18.9 21.0 12.5 5.1 4.02
91

Table 48. Coworker communication in SSG for each response option (%) and item average (on a 6-point scale)

Everyone in my crew...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

has confidence in each other to 

work safely

1.4 2.6 6.0 14.0 38.5 37.5 4.98

helps each other with H&S 

problems at work

0.8 2.1 3.8 13.6 42.2 37.6 5.07

informs each other about 

potential workplace H&S 

hazards

0.8 1.3 3.1 11.6 37.5 45.7 5.21

Table 49. Supervisor support for H&S in SSG for each response option (%) and item average (on a 6-point scale)

My supervisors...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

try to help me do my job as 

safely as possible

1.6 3.2 4.7 14.0 32.6 43.8 5.04

help me if I have a H&S 

problem at work

1.4 2.5 5.4 13.0 37.1 40.6 5.04

don’t notice if I do my job 

safely

32.9 25.3 12.5 12.2 10.9 6.2 4.39
92

Table 50. Supervisor communication in SSG for each response option (%) and item average (on a 6-point scale)

My supervisors...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average

remind me to follow H&S 

work rules

1.9 2.7 5.8 13.9 39.7 36.1 4.95

closely monitor my H&S work 

practices

3.3 5.5 10.9 24.9 33.6 21.8 4.45

take action if I don’t follow 

H&S work practices

2.4 2.9 7.0 16.4 37.5 33.8 4.85

clearly explain H&S rules to 

me

1.9 3.0 7.9 15.4 37.5 34.3 4.86

regularly inform me of work 

hazards specific to my job

3.7 5.1 9.5 19.2 32.2 30.3 4.62

encourage communication 

about H&S problems

2.6 2.9 7.5 16.3 33.0 37.5 4.87

I am satisfied with my 

supervisor’s H&S management 

4.6 4.1 6.3 14.3 33.1 37.6 4.80
93

Table 51. Worker engagement in SSG for each response option (%) and item average (on a 6-point scale)

When it comes to the H&S 

rules...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average

the same rules apply to all 

employees

6.6 4.7 5.6 11.0 24.3 47.8 4.85

I can question the 

rules/procedures that influence 

my work

4.5 5.6 7.7 16.1 33.9 32.2 4.66

concerns are heard before 

making new rules or 

procedures

6.6 7.0 10.1 19.2 31.4 25.8 4.39

I am involved in improving 

H&S rules and procedures

5.7 8.8 13.0 20.4 28.2 23.9 4.28

Table 52. H&S knowledge in SSG for each response option (%) and item average (on a 6-point scale)

I know how to...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

use H&S equipment to follow 

standard work procedures

0.3 0.4 2.4 7.6 38.1 51.3 5.37

maintain or improve workplace 

H&S

0.4 0.6 2.3 10.6 43.3 42.8 5.24

reduce the risk of workplace 

H&S incidents at my job

0.1 1.1 1.9 9.9 39.8 47.2 5.30
94

Table 53. H&S motivation in SSG for each response option (%) and item average (on a 6-point scale)

It is important to...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

maintain workplace health and 

safety at all times

0.6 0.3 1.0 3.3 22.1 72.7 5.64

reduce the risk of workplace 

H&S incidents at my job

0.4 0.4 0.9 3.4 22.2 72.6 5.64

maintain or improve my 

personal H&S

0.6 0.4 0.6 4.0 21.0 73.5 5.65

Table 54. H&S training adequacy in SSG for each response option (%) and item average (on a 6-point scale)

When it comes to H&S 

training...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

this site provides enough 

training for me to do my job

1.9 2.6 4.7 12.3 35.7 42.8 5.06

it helps me do my job as 

healthy/safely as I can

1.1 1.5 3.9 11.2 38.0 44.3 5.16

it is not a priority here 57.7 19.6 6.2 6.2 6.5 3.8 5.05
95

Table 55. Adaptability in SSG for each response option (%) and item average (on a 6-point scale)

In general I think that...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

tried and tested ways of doing 

things are usually the best

3.2 5.3 10.6 25.3 32.9 22.7 4.47

I can handle any changes that 

come along

0.6 1.1 4.0 17.4 46.7 30.2 4.99

changes in my work routine 

keep my job interesting

3.3 4.2 7.6 19.1 39.4 26.3 4.66
96

Appendix F: Overall Results/Averages for

Industrial Minerals Industry (n = 907)
97

Table 56. Proactivity in industrial minerals for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

go out of my way to address 

potential hazards

1.1 1.3 6.2 18.9 33.7 38.7 4.99

voluntarily carry out tasks that 

help improve H&S

0.7 1.3 4.8 19.1 38.7 35.4 5.00

make suggestions to improve 

how H&S is handled

1.0 2.9 10.3 24.7 36.5 24.6 4.67

try new things to improve 

workplace H&S

1.3 2.8 11.0 26.5 33.3 25.2 4.63

try to solve problems in ways 

that reduce H&S risks

0.9 1.6 6.5 19.3 36.2 35.5 4.95

Table 57. Compliance in industrial minerals for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

don’t take risks that could 

result in an accident

0.6 1.7 4.3 10.5 26.1 56.9 5.31

use all necessary H&S 

equipment to do my job

0.8 1.2 2.7 11.6 28.5 55.3 5.32

use the correct H&S 

procedures for carrying out my 

job

0.8 0.6 3.1 9.5 32.0 54.0 5.33

always report all H&S-related 

incidents

1.1 1.1 5.0 11.0 25.9 55.9 5.27
98

Table 58. Sense of control in industrial minerals for each response option (%) and item average (on a 6-point scale)

When I’m at work I...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

I can pretty much achieve 

whatever I set out to do

1.1 0.4 4.2 13.5 40.9 39.8 5.12

I can do something if I am 

unhappy about a decision

4.8 4.4 9.7 22.3 36.9 21.8 4.48

I can stay healthy/safe if I take 

the right actions

0.9 0.7 1.8 7.1 31.2 58.4 5.42

most problems that I 

experience are “out of my 

hands”

14.1 21.0 18.8 21.2 14.9 10.1 3.68

Table 59. Thoroughness in industrial minerals for each response option (%) and item average (on a 6-point scale)

When doing my job...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

I am always thorough 1.2 1.7 5.9 24.5 45.0 21.7 4.76

I can be somewhat careless 

with my work tasks

40.7 30.1 10.8 9.1 6.5 2.8 4.81

I'm a reliable worker 1.4 0.2 0.9 2.3 25.2 69.9 5.59

I work until my task is finished 1.0 0.8 1.2 8.7 33.2 55.0 5.38

I know when to seek help 

during a difficult task

0.8 0.7 2.8 7.3 32.8 55.5 5.37
99

Table 60. Risk tolerance in industrial minerals for each response option (%) and item average (on a 6-point scale)

As far as day to day work...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

I do not take risks with my 

safety/health

2.2 1.7 3.7 11.4 29.8 51.2 5.19

I take risks regularly 54.2 27.8 7.3 4.3 3.3 3.1 5.16

safety comes first 0.9 0.4 1.9 6.5 24.5 65.7 5.50

I prefer to avoid risks 1.4 1.4 1.7 8.3 28.1 59.0 5.37

Table 61. Organizational support for H&S in industrial minerals for each response (%) and item average (on a 6-point scale)

As far as day to day work...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

H&S rules and procedures are 

sometimes ignored

30.2 24.9 12.1 15.6 12.1 5.1 4.30

it doesn’t matter how the work 

is done if there are no accidents

54.3 24.0 7.5 5.4 4.2 4.6 5.05

I often have impossible 

production pressures

25.6 25.8 16.6 16.0 9.8 6.2 4.23
100

Table 62. Coworker communication in industrial minerals for each response (%) and item average (on a 6-point scale)

Everyone in my crew...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

has confidence in each other to 

work safely

1.9 2.0 5.4 15.8 39.4 35.5 4.95

helps each other with H&S 

problems at work

1.2 1.7 5.1 14.2 41.2 36.6 5.02

informs each other about 

potential workplace H&S 

hazards

0.9 1.0 4.4 12.5 37.4 43.8 5.16

Table 63. Supervisor support for H&S in industrial minerals for each response (%) and item average (on a 6-point scale)

My supervisors...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

try to help me do my job as 

safely as possible

2.2 2.1 4.7 10.9 30.5 49.1 5.14

help me if I have a H&S 

problem at work

2.1 1.7 4.5 9.3 34.4 48.0 5.16

don’t notice if I do my job 

safely

34.0 29.5 10.1 9.8 9.4 7.2 4.47
101

Table 64. Supervisor communication in industrial minerals for each response (%) and item average (on a 6-point scale)

My supervisors...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

remind me to follow H&S 

work rules

2.1 3.1 5.3 12.5 34.7 42.3 5.01

closely monitor my H&S work 

practices

3.5 6.8 11.9 23.8 31.9 22.1 4.40

take action if I don’t follow 

H&S work practices

2.6 3.1 6.9 16.6 38.6 32.3 4.82

clearly explain H&S rules to 

me

2.4 4.1 6.7 15.0 35.1 36.7 4.86

regularly inform me of work 

hazards specific to my job

3.4 4.9 10.4 17.7 30.9 32.6 4.66

encourage communication 

about H&S problems

2.9 3.2 6.8 13.7 33.7 39.7 4.91

I am satisfied with my 

supervisor’s H&S management 

4.0 3.8 5.3 12.3 32.4 42.1 4.92
102

Table 65. Worker engagement in industrial minerals for each response (%) and item average (on a 6-point scale)

When it comes to the H&S 

rules...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

the same rules apply to all 

employees

5.5 3.4 6.2 7.8 24.9 52.1 4.99

I can question the 

rules/procedures that influence 

my work

5.0 5.7 6.0 14.8 32.4 36.1 4.72

concerns are heard before 

making new rules or 

procedures

4.4 4.7 10.2 19.1 32.2 29.4 4.58

I am involved in improving 

H&S rules and procedures

6.2 7.1 13.0 23.9 27.8 22.0 4.26

Table 66. H&S knowledge in industrial minerals for each response (%) and item average (on a 6-point scale)

I know how to...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

use H&S equipment to follow 

standard work procedures

0.4 0.3 2.3 7.5 36.1 53.2 5.38

maintain or improve workplace 

H&S

0.4 0.8 3.2 12.8 38.2 44.6 5.21

reduce the risk of workplace 

H&S incidents at my job

0.6 0.4 3.0 12.8 38.5 44.6 5.22
103

Table 67. H&S motivation in industrial minerals for each response (%) and item average (on a 6-point scale)

It is important to...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

maintain workplace health and 

safety at all times

0.2 0.2 1.4 4.9 20.1 73.1 5.64

reduce the risk of workplace 

H&S incidents at my job

0.2 0.0 1.1 5.6 21.5 71.6 5.63

maintain or improve my 

personal H&S

0.3 0.2 1.6 4.2 20.0 73.7 5.64

Table 68. H&S training adequacy in industrial minerals for each response (%) and item average (on a 6-point scale)

When it comes to H&S 

training...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

this site provides enough 

training for me to do my job

0.9 0.9 4.0 8.3 32.0 53.9 5.31

it helps me do my job as 

healthy/safely as I can

0.6 1.6 2.9 7.7 34.1 53.2 5.33

it is not a priority here 69.6 14.2 3.9 5.2 3.8 3.3 5.31
104

Table 69. Adaptability in industrial minerals for each response option (%) and item average (on a 6-point scale)

In general I think that...

Strongly 

Disagree

Disagree Somewhat 

Disagree

Somewhat 

Agree

Agree Strongly 

Agree

Average 

tried and tested ways of doing 

things are usually the best

3.2 5.7 12.3 26.0 32.0 20.8 4.40

I can handle any changes that 

come along

0.7 1.0 4.5 15.8 46.8 31.3 5.01

changes in my work routine 

keep my job interesting

3.1 3.6 9.0 21.2 36.9 26.3 4.64
105

Appendix G: Relative Weights Results

by Coal Mining Subsector
106

Table 70. Impact of safety climate constructs on worker performance (proactivity and compliance), knowledge, and 

motivation in the coal mining industry

Construct

RS-RW

Proactivity 

R

2 = 37.06%

RS-RW (%)

Compliance 

R

2 = 49.17%

RS-RW (%)

Motivation

R

2 = 38.15%

RS-RW (%)

Knowledge

R

2 = 57.97%

RS-RW (%)

Organizational H&S support 4.10* 5.96* 6.64* 3.22

Supervisor H&S support 5.59* 4.46* 3.37 5.04

Supervisor communication 10.55* 9.08* 7.09* 17.19

Coworker communication 10.94* 6.87* 15.16* 9.39

Worker engagement 7.74* 8.47* 5.28* 17.56

H&S training 8.48* 8.54* 16.39* 13.60

Sense of control 11.69* 8.16* 6.28* 4.59

Thoroughness 21.48* 17.88* 13.94* 13.29

Risk tolerance 12.98* 26.36* 14.81* 8.89

Adaptability 6.45* 4.21* 11.04* 7.22

*Statistically significant at the p = .05 level.
107

Table 71. Impact of safety climate constructs on H&S outcomes in the coal mining industry

Construct

RS-RW

Near misses

R

2 = 10.89%

RS-RW (%)

First aid

R

2 = 8.22%

RS-RW (%)

Med. treatment

R

2 = 7.95%

RS-RW (%)

Days lost

R

2 = 8.55%

RS-RW (%)

Organizational H&S support 23.70* 44.31* 26.75* 21.15

Supervisor H&S support 11.42 4.07 4.40 5.30

Supervisor communication 4.03 3.21 3.49 3.14

Coworker communication 4.76 1.66 3.49 2.81

Worker engagement 11.11 15.91 18.03 17.17

H&S training 5.06 8.29 11.26 6.18

Sense of control 2.42 8.71 8.50 5.91

Thoroughness 17.36 7.90 20.24 31.87*

Risk tolerance 14.75 2.11 3.03 3.29

Adaptability 5.42 3.80 0.90 3.16

*Statistically significant at the p = .05 level.
108

Appendix H: Relative Weights Results

by SSG Mining Subsector 
109

Table 72. Impact of safety climate constructs on worker performance (proactivity and compliance), knowledge, and 

motivation in the stone, sand, and gravel industry

Construct

RS-RW

Proactivity 

R

2 = 31.81%

RS-RW (%)

Compliance 

R

2 = 44.40%

RS-RW (%)

Motivation

R

2 = 43.16%

RS-RW (%)

Knowledge

R

2 = 49.29%

RS-RW (%)

Organizational H&S support 4.18* 2.04* 1.48* 4.18*

Supervisor H&S support 6.36* 2.77* 4.88* 6.36*

Supervisor communication 5.46* 4.88* 9.62* 5.46*

Coworker communication 9.54* 7.20* 13.34* 9.54*

Worker engagement 9.69* 4.21* 4.44* 9.67*

H&S training 5.68* 4.34* 13.87* 9.34*

Sense of control 21.76* 9.29* 9.89* 8.50*

Thoroughness 18.47* 23.41* 22.42* 17.67*

Risk tolerance 12.20* 31.41* 20.52* 14.19*

Adaptability 6.30* 1.77* 11.92* 11.18*

*Statistically significant at the p = .05 level.
110

Table 73. Impact of safety climate constructs on H&S outcomes in the stone, sand, and gravel industry

Construct

RS-RW

Near misses

R

2 = 7.3%

RS-RW (%)

First aid

R

2 = 5.97%

RS-RW (%)

Med. treatment

R

2 = 7.92%

RS-RW (%)

Days lost

R

2 = 6.54%

RS-RW (%)

Organizational H&S support 29.47* 30.08* 33.79* 39.49*

Supervisor H&S support 6.46* 5.10 3.69 5.95*

Supervisor communication 2.20 1.67 2.01 2.64

Coworker communication 1.49 1.58 1.57 1.47

Worker engagement 4.29 0.92 1.15 1.17

H&S training 6.16* 4.47 3.93* 2.33

Sense of control 1.91 1.78 1.74 1.99

Thoroughness 20.29* 21.60* 19.81* 18.21*

Risk tolerance 26.54* 31.66* 25.81* 17.71*

Adaptability 1.16 1.11 6.47* 9.00*

*Statistically significant at the p = .05 level.
111

Appendix I: Relative Weights Results

by Industrial Minerals Subsector
112

Table 74. Impact of safety climate constructs on worker performance (proactivity and compliance), knowledge, and 

motivation in the industrial minerals industry

Construct

RS-RW

Proactivity 

R

2 = 34.63%

RS-RW (%)

Compliance 

R

2 = 49.08%

RS-RW (%)

Motivation

R

2 = 37.53%

RS-RW (%)

Knowledge

R

2 = 52.29%

RS-RW (%)

Organizational H&S support 1.10* 1.88* 2.26* 2.88*

Supervisor H&S support 3.99* 3.47* 5.81* 9.05*

Supervisor communication 4.63* 4.04* 6.28* 10.83*

Coworker communication 9.68* 13.33* 8.78* 10.46*

Worker engagement 20.91* 4.75* 6.68* 14.97*

H&S training 5.94* 5.55* 23.55* 17.85*

Sense of control 12.01* 8.53* 8.78* 9.13*

Thoroughness 20.58* 25.67* 13.01* 10.52*

Risk tolerance 13.28* 29.28* 13.24* 5.99*

Adaptability 7.85* 3.49* 11.57* 8.30*

*Statistically significant at the p = .05 level.
113

Table 75. Impact of safety climate constructs on H&S outcomes in the industrial minerals industry

Construct

RS-RW

Near misses

R

2 = 11.66%

RS-RW (%)

First aid

R

2 = 8.56%

RS-RW (%)

Med. treatment

R

2 = 9.81%

RS-RW (%)

Days lost

R

2 = 9.83%

RS-RW (%)

Organizational H&S support 36.39* 21.92* 30.09* 22.11*

Supervisor H&S support 6.62* 2.68 3.49 3.73

Supervisor communication 3.67 2.18 3.41 4.37

Coworker communication 2.34 2.02 2.85 2.12

Worker engagement 2.44 2.62 5.96 4.87

H&S training 25.11* 32.24* 25.35* 36.81*

Sense of control 5.05 4.96 5.11 4.39

Thoroughness 4.43 19.49* 18.45* 16.37*

Risk tolerance 13.38* 10.04* 3.65 4.20

Adaptability 0.52 1.82 1.62 0.99

*Statistically significant at the p = .05 level.
114

Appendix J: Management Communication Scorecard

for Establishing and Maintaining Visibility
115 Communication strategy

Management Objectives

Evaluation and action plan

Communication quality indicators Ways to improve

Scorecard

Measurement Target

Establish and 

maintain 

management 

visibility

Support worker H&S 

initiatives 

Follow through and do 

what you say you will do

Focus on quality over of 

quantity of interactions

Actively listen to worker 

concerns

• # workers talk to about risks on 

the job (pre/mid/post shift)

• # workers follow up with 

pre/mid/post shift

• # work orders put in based on 

risk assessment discussions

• # medium to high-risk hazards 

workers identify to you

• # hazards mitigated with the 

help of workers

• # one-on-one interactions/ 

reminders with workers

• # of positive H&S things found/ 

observed that workers are doing

• # risk assessments turned in

• # risk assessments mitigated

• List proactive discussions with workers about 

risk management

• Leave conversations on a 

positive note

• Balance listening and 

action

• Focus on specific hazards 

and warnings

• Discuss individual 

sampling results with 

workers

• Explain rules and the 

reason(s) behind their 

implementation

• List discussion topics had with workers about 

hazards, risks and mitigation efforts 

• List work orders fixed, what determined priority 

and average time it takes to address these issues

• List of common hazards identified, when, and 

where

• List of hazards mitigated and how, who took the 

lead, and how long it took to address

• Common one-on-one topics discussed

• Best practices identified with workers

• Types of incidents prevented through RAs

• New methods/tools used to assess risk

Indicators for visible communication to the workforce

Assessment for this communication objective:

Document indicators currently being improved:

__________________________________________________________

__________________________________________________________

__________________________________________________________

Poor, need to 

improve 

immediately

Moderate but 

needs 

improvement

Adequate but 

have gaps

Good but always 

room for 

improvement

Very good, 

maintaining 

objectives
116

Appendix K: Management Communication

Scorecard for Establishing and Maintaining

Consensus among the Workforce
117 Communication strategy

Management objectives

Evaluation and action plan

Communication quality indicators Ways to improve

Scorecard

Measurement Target

Establish and 

maintain 

consensus 

among the 

workforce

Obtain trust and buy-in 

from the workforce

Support worker execution 

of H&S practices

Engage workers in H&S 

decision making

Enhance workers’ 

responsibility and 

accountability on the job

• # workers involved in a new 

process

• # of tours or observations 

performed by H&S committee

• # risks or hazards found during 

H&S observations/tours

• # of leadership development 

opportunities for workers

• # of peer-to-peer interventions 

performed/facilitated 

• List methods/tools used to empower and 

involve workers

• Establish a balance of 

hourly and salaried 

workers on all decisionmaking committees

• Establish a safety team 

that has primarily hourly 

representatives 

• Develop new programs 

for self and peer 

evaluation, provide 

feedback on all 

assessments

• List hazards and risks commonly found and 

reported by hourly employees

• Trends in reported hazards and mitigation 

strategies

• Leadership development opportunities 

identified for workers, including frequency

• How peers evaluate each other, common 

hazards identified, and corrective actions taken

Indicators for communication engagement with the workforce

Assessment for this communication objective:

Document indicators currently being improved:

__________________________________________________________

__________________________________________________________

__________________________________________________________

Poor, need to 

improve 

immediately

Moderate but 

needs 

improvement

Adequate but 

have gaps

Good but always 

room for 

improvement

Very good, 

maintaining 

objectives
118

Appendix L: Management Communication Scorecard for

Establishing Consistent Communication with the Workforce
119 Communication strategy

Management objectives

Evaluation and action plan

Communication quality indicators Ways to improve

Scorecard

Measurement Target

Establish and 

maintain 

consistency 

of the H&S 

management 

system

Balance proactive and 

reactive communication

Sustain proactive and 

reactive communication

Balance positive and 

negative reinforcements 

Balance positive and 

negative consequences

Establish high-quality 

communication mediums

• # basic observations (positive or 

negative) used to give feedback

• Discretionary system used to 

reward safety values

• # of crew-based meetings 

throughout the week

• # of risk assessment, near miss, 

or other forms completed

• # of reported issues that were 

discussed with workforce

• # of corrective action reports

• # of targeted injuries reduced or 

prevented

• Develop safety standards, new task training, 

and feedback in response to observations

• Ask employees what is/is 

not working on the job

• Establish a value-based

reward program grounded 

in communicative support

• Establish a script for preshift meetings so the same 

messages are 

communicated across shifts

• Have daily management 

meetings to ensure 

consistent communication 

with the workforce 

throughout the day

• Methods and types of recognition programs for 

workers

• Types of messages communicated in pre-shift 

meetings and hazard noted across shifts

• List of risks identified within an RA matrix

• List of issues reported and how they were 

resolved, including how long it took to follow up

• List corrective actions made

• Specific scenarios where injuries have been 

prevented based of changes made

Indicators for consistent communication with the workforce

Assessment for this communication objective:

Document indicators currently being improved:

__________________________________________________________

__________________________________________________________

__________________________________________________________

Poor, need to 

improve 

immediately

Moderate but 

needs 

improvement

Adequate but 

have gaps

Good but always 

room for 

improvement

Very good, 

maintaining 

objectives
Promoting productive workplaces through safety and health research

DHHS (NIOSH) Publication No. 2020-120

DOI: https://doi.org/10.26616/NIOSHPUB2020120