Measuring and Managing Situational Awareness

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While workers are not typically intentional risk-seekers, they do sometimes take risky decisions. One possible reason for taking these decisions could be the lack of situational awareness among workers. Simply, situational awareness is the ability to identify relevant information from the environment, understanding that information, and estimating potential outcomes that can happen.

Within safety context, situational awareness relates to the ability of being able to identify hazards in the environment, understanding the risk associated with the hazards, estimating the chances of an accident occurring due to the hazards, and process changing safety information. Any breakdown in this process can lead to poor decisions by workers despite receiving all the necessary safety training or daily pre-task safety meeting. Work on construction sites is highly dangerous and ever-changing. Therefore, we need to be able to measure situational awareness in real-time and find out what factors reduce situational awareness among workers.

This project has two key objectives:

  1. Measure the situational awareness of workers within the electrical sector.
  2. Identify the influence of various work-related leading indicators on the situational awareness.

BENEFICIAL OUTCOMES FROM THIS PROJECT

  1. This project will benchmark the existing level of situational awareness of workers in the electrical sector.
  2. This project will provide a scientifically-validated tool to measure situational awareness that can used at any time to test the effectiveness of a safety meeting or new training program (e.g., Virtual Reality) and safety resources.
  3. The responses to these questions can be measured against the performance of safety managers/professionals to identify skill deficiencies among workforce to develop targeted and customized training programs.
  4. Identify factors that reduce workers situational awareness and bring about measures to control for such factors.
  5. In future, the data can be used to identify and predict high-risk conditions and scenarios respectively.

For more information on the project, please contact Sid Bhandari at siddharth.bhandari@wmich.edu or (303)-350-7685.

Research StatusData Collection

Funding AgencyELECTRI International

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