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The National Institute for Occupational Safety and Health (NIOSH)





Mining Project: Evaluation of VR Mine Rescue Training Platform
Keywords: Computer simulation Group training Mine rescue teams
Principal Investigator
Jennica Bellanca -  Request informationStart Date
10/1/2023Objective
Recent research suggests that a significant portion of mine rescue team members do not feel fully prepared to respond in the event of an emergency. Additionally, mine rescue teams face challenges of high turnover and low recruitment. However, high-fidelity, holistic training (e.g., full-scale Mine Emergency Response Drill) is expensive in both time and resources and may not be available to all mine rescue teams. Virtual reality (VR) has the potential to supplement current mine rescue training and help fill this gap. Previous research shows that VR can help increase engagement, learning, and retention. However, the mining industry has not widely adopted VR. It is unclear what barriers to implementation exist, if adaptations of the possible interventions are necessary, and if VR training for mine rescue is effective.Topic Areas
Education and Training
Rescue Technologies and Training
Research Summary

Approach
This project aims to evaluate NIOSH’s recently developed VR Mine Rescue Training platform (VR-MRT) as a supplemental training tool. Researchers will use the RE-AIM framework, which assesses the **R**each, **E**ffectiveness, **A**doption, **I**mplementation, and **M**aintenance of interventions. The study will measure improvements in mine rescue preparedness, identify challenges and barriers to adoption and implementation, and suggest strategies to address them. The evaluation will include effectiveness experiments (i.e., comparing VR-MRT and traditional training to traditional training alone), longitudinal implementation interviews and observations, and organizational readiness surveys. Researchers plan to work with collegiate mine rescue teams, mining companies, training centers, and government agencies. These studies will largely be conducted at the training location with some follow-up electronically or over the phone. The evaluations will be completed semi-concurrently using mixed methods (i.e., integrating qualitative and quantitative methods).
Using the evaluation results, NIOSH will modify VR-MRT and release it as a stand-alone software package that other mine rescue teams, mines, and training centers can adopt and implement to augment their current training. To help address the question of broader VR adoption, researchers will also explore future VR-related opportunities for health and safety applications (e.g., new miner training, outreach). This will involve investigating leads from previous projects, benchmarking NIOSH's VR initiatives against those in other countries and industries, and incorporating feedback from the evaluations.
Milestones and Accomplishments
Description
Audience
YearWill release Beta version of VR Mine Rescue Training (VR-MRT) Platform
Mine rescue teams, trainers, health and safety professionals
2024Will complete effectiveness evaluation of VR-MRT
Mine rescue teams, trainers, health and safety professionals
2025Will complete implementation evaluation of VR-MRT
Mine rescue teams, trainers, health and safety professionals
2027Planned Impacts and Outcomes
Overall, the goal of this project is to complete the development and evaluation of VR-MRT as a supplemental training tool to prepare mine rescue teams more effectively for the challenging and dangerous work required to enhance the post-disaster survivability of mineworkers. Ideally, the increased adoption and implementation VR-MRT and other VR applications will improve mine rescue response efficiency and reduce harm to mine rescue teams and mineworkers.
In the short term, the successful completion of this project has the potential to facilitate the enrichment of mine rescue training at the project’s target sites with new content and more engaging training. VR-MRT may also help make training more accessible to these sites by overcoming many of the logistical challenges (e.g., training frequency, training cost) that mine rescue teams face. Beyond the study participants, VR-MRT has the potential to enrich mine rescue training worldwide. As evidenced by queries about its availability and requests to incorporate it into training, it is expected that many teams/companies will be interested in incorporating VR-MRT once it is fully released.
In the long term, the successful implementation of VR-MRT has the potential to increase the development and implementation of additional VR content (e.g., surface mine rescue, introduction to mining, inspector training). The strategies to overcome challenges and barriers to adoption and implementation of VR-MRT could improve future implementation efforts, facilitating wider and faster use and impact. Furthermore, this work has the potential to serve as a case study for implementation research. The success of this model will aid in the incorporation of implementation science in occupational health and safety research and contribute to the improvement of the effectiveness and impact of mining research in general.
Supporting Visuals
A two-part graphic. On the left is a screenshot of the simulation module of a virtual reality mine rescue training platform. On the right is a photo of mine rescue team members wearing head-mounted displays. Both the screenshot and photo represent rescue team members reviewing a map in order to decide what to do next.
A screenshot of the simulation module of VR-MRT next to a picture of mine rescue team members wearing head-mounted displays. Both show team members reviewing the map in order to decide what to do next.

See Also
Assessing the Effects of Virtual Emergency Training on Mine Rescue Team Efficacy
Development and Application of Reservoir Models and Artificial Neural Networks for Optimizing Ventilation Air Requirements in Development Mining of Coal Seams
Exploring Virtual Mental Practice in Maintenance Task Training
Mine Emergency Response Command Center Training Using Computer Simulation
Modeling and Prediction of Ventilation Methane Emissions of U.S. Longwall Mines Using Supervised Artificial Neural Networks
Modernization and Further Development of the NIOSH Mine Emergency Response Training System (MERITS), Phase 1
New Simulated Gas Detector Offers Realistic Training for Mine Rescue Teams
SPONCOM - A Computer Program for the Prediction of the Spontaneous Combustion Potential of an Underground Coal Mine
Technology News 545 - NIOSH Updates Spontaneous Combustion Assessment Software
Technology News 549 - MFIRE 3.0 - NIOSH Brings MFIRE into 21st Century
Page last reviewed: November 14, 2023
Page last updated: November 14, 2023
Content source: National Institute for Occupational Safety and Health, Mining Program
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