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The National Institute for Occupational Safety and Health (NIOSH)





Mining Project: Analysis of Health and Safety Management System Practices Through Multilevel Interventions
Keywords: Health and safety management Risk analysis
This page is archived for historical purposes and is no longer being maintained or updated.
Principal Investigator
Emily Haas -  Request informationStart Date
10/1/2014End Date
9/30/2019Objective
Identify and characterize health and safety performance practices—through worker-technology-management interactions—to provide guidance about risk management processes with a focus on: (1) accurate identification and management of site-wide risks; and (2) improvement in organizational and individual H&S values through empowering initiatives on site, in order to understand how health and safety risk management tools and technologies can influence workers' health and safety perceptions and behaviors through appropriate implementation on site.Topic Areas
Education and Training
Emergency Management
Respirable Dust
Respiratory Diseases
Research Summary

Research is needed that informs the industry about what risk management practices are important for mine worker health and safety (H&S) performance and how those practices can be developed, implemented, and maintained over time as part of a continuous organizational process within a site's respective health and safety management system (HSMS). One of the possible reasons why HSMS is not fully integrated in the mining industry is because perspectives of the worker and of mine site leadership have not been considered together to fully understand and manage risk-based problems.
To address these issues, this project had three research aims:
Determine the most important organizational values and individual characteristics that influence miners’ proactive safety/health performance.
Develop and test multilevel interventions that use safety/health technology as a risk management tool to identify, understand, and improve how organizational leadership and communication practices influence worker perceptions and subsequent behaviors.
Draft pilot health and safety management tools to inform communication and risk assessment efforts at different levels of the organization.Under this project research, multilevel interventions (MLIs) were designed to follow a sample of workplaces over time, while measuring the utilization of health and safety practices by leaders and workers and behavioral outcomes of interest at the workplace and at worker levels. The interventions focused on measurable problems within the mining industry to assess the utility of the multilevel framework. Specifically, NIOSH researchers analyzed what and how organizational and supervisor health and safety practices influenced worker perceptions of their organizations’ H&S values and how these perceptions impacted their subsequent H&S behaviors.
Throughout the project case studies, interventions and longitudinal evaluations were used to identify tangible methods to bridge the safety/health interactions between workers and management and improve the future implementation of organizations’ risk management processes.
Specifically, four overarching issues were addressed throughout this research, as detailed below.
(1) How Technology and Support from Leadership Impact Workers’ Health/Safety Behaviors, Including Those That Lower Exposure to Dust
Historically, new technologies have been introduced in the mine environment with little known about how to effectively integrate these tools to control risk to the lowest achievable level. Project findings have shown workers’ progression toward adopting technologies as well as gaps in management-worker performance with technology. Project outputs were intended to minimize adoption time among workers and organizations and minimize unintended consequences and disruption to workers’ situational awareness (all while simultaneously revealing H&S hazards unknown to the mine).
*For an overview of results, see these publications:*
Infographics: Helping Mines Control Respirable Silica Dust
Selected Publications on EVADE Software, Helmet-CAM, Dust Exposure, and Behavioral Studies
Haas EJ, Cecala AB, Colinet JF [2019]. Comparing the implementation of two dust control technologies from a sociotechnical systems perspective. Mining, Metallurgy & Exploration. August Issue, Vol. 36, No. 4, pp. 709–727.
Haas EJ [2019]. Using self-determination theory to identify organizational interventions to support coal mineworkers’ dust-reducing practices. International Journal of Mining Science and Technology, Vol. 29, No. 3, pp. 371–378. https://doi.org/10.1016/j.ijmst.2019.02.001
Haas E and Colinet J [2018]. Miners implement corrective actions in response to CPDM dust data. Coal Age, Vol. 123, No. 2, pp. 36–38.
Haas E and Helton J [2017]. How miners in low coal respond to the CPDM. Mining People Magazine, April/May Issue, pp. 42–44.
(2) Aspects of Safety Climate That Impact Workers’ Perceptions of Their Organizations’ Values
Part of this effort included the execution of a safety climate survey to assess workers’ perceptions at their respective mine operations. Participants consisted of 2,683 mineworkers at 39 mine sites. The results provided 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 more influential safety climate constructs in predicting workers’ performance. These results also showed 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’ personal-based factors on the job. The statistical results of the survey data are highlighted below:
All 10 safety climate constructs were 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 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%.*For an overview of results, see these publications:*
Haas EJ, Yorio PL [2019]. The role of risk avoidance and locus of control in workers’ near miss experiences: Implications for safety management systems. Journal of Loss Prevention in the Process Industries, Vol. 59, pp. 91–99.
Haas EJ, Ryan M, Hoebbel CL [2018]. Job autonomy and safety climate: Examining associations in the mining industry. Professional Safety, December Issue, pp. 30–34.
Haas EJ, McGuire  J,  Hoebbel CL [2017]. Workplace perceptions of safety: What do your workers think about health and safety, why does it matter, and what can you do about it? Rock Products, May Issue, pp. 26–27, 30, 32.
(3) Managers’ Effective Use of Various Risk Management Practices to Facilitate Workers’ Health/Safety Performance
Occupational H&S interventions have been linked to safety but have had minimal impact in bringing about sustainable change. This lack of effectiveness has been attributed to disconnected interventions across the industry, a lack of communication and dissemination of solutions, and an absence of documented processes and practices that the mining industry can use. To that end, this project sought to understand how communication among organizational leadership can influence worker behaviors and perceptions of the organization.
*For an overview of results, see these publications:*
Haas EJ [2020]. The role of supervisory support on workers’ health and safety performance. Health Communication, Vol. 35, No. 3, pp. 364–374.
Haas EJ, McGuire J, Hoebbel C, Bohm S [2019]. A comparison of supervisor-worker communication in differing work environments. Aggregates Manager, April Issue, Vol. 24, No. 4. pp. 10–12.**
Haas E J [2018]. Applying the precaution adoption process model to the acceptance of mine safety and health technologies. Occupational Health Science, Vol.  2, No. 1, pp. 43–66.
Haas EJ, Connor BP, Vendetti J, Heiser R [2018]. A case study exploring field-level risk assessments as a leading safety indicator. Transactions of the Society for Mining, Metallurgy & Exploration, Vol. 342, pp. 22–28.
Rost KA, Willmer DR, Haas EJ [2015]. An operant analysis of leadership practices in mining. Journal of Safety, Health and Environmental Research, Vol. 11, No. 2, pp. 234–241.
(4) General Practices to Improve and Maintain Organizations’ Tailoring of Their Own HSMS
At the culmination of the project, NIOSH determined that organizational and personal safety climate factors can impact H&S performance to varying degrees. Because other studies have already conveyed the significant, positive relationship among HSMS elements, such as safety climateand safety performance, 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. Specifically, the project research provided guidance for improving organizational factors to help enhance the overall culture. Organizations can now start to address a select number of HSMS practices and, over time, scale their system to include additional indicators.
*For an overview of results, see these publications:*
Haas EJ, Eiter B, Hoebbel C, Ryan ME [2019]. The impact of job, site, and industry experience on worker health and safety. Safety, Vol. 5, No. 16, 21 p. doi:10.3390/safety5010016
Haas EJ, McGuire J [2019]. Tracking communication as a performance measure: The industry’s health and safety requirements are evolving and new tools are needed. Rock Products, August Issue, pp. 132–134.
Haas E J, Ryan M, Willmer DR [2018]. An examination of mining companies’ online health and safety policies: implications for improving risk management. Journal of Safety, Health and Environmental Research, Vol. 14, No. 1, pp. 337–347.
Haas EJ, Yorio PL [2016]. Exploring the state of health and safety management system performance measurement in mining organizations. Safety Science, Vol. 83, pp. 48–58.
Related Project Research
Within a new related project, Validating H&S Leading Indicators to Identify and Mitigate Risks in the Mining Industry, which started in October 2019, NIOSH is using mobile technology to identify and aggregate behavioral and process leading indicators that are critical to preventing H&S incidents and mine emergencies. The use of machine learning will reveal important areas of intervention to prevent incidents and, as a result, research will aim to integrate the use of leading indicators in daily work practices and eventually operationalize HSMS practices across the mining industry.

See Also
An Analysis of Health and Safety Management Systems in Mining
Assessing the Safety Culture of Coal Mining
Enhanced Utilization of Personal Dust Monitor Feedback
Safety Culture Assessment in Underground Coal Mining
Validating H&S Leading Indicators to Identify and Mitigate Risks in the Mining Industry
Page last reviewed: February 21, 2020
Page last updated: February 21, 2020
Content source: National Institute for Occupational Safety and Health, Mining Program
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