HAZMAT Technician-level Emergency Response: A Mental Model Framework for Radiological Dispersal Device (RDD) Incidents

Author:

Leek Angela E.,Keren Nir,Blumenthal Daniel1,Irwin William2,Musolino Stephen3

Affiliation:

1. US Department of Energy, Washington, DC

2. Department of Health, State of Vermont, Burlington VT

3. Brookhaven National Laboratory, Upton, NY (retired).

Abstract

Abstract This research examines the cognitive frameworks used by HAZMAT technicians when responding to incidents involving Radiological Dispersal Devices (RDDs), which are conventional explosive devices with radioactive materials incorporated. The objective is to introduce the Expected Mental Model State (EMMS) as a comprehensive evaluation tool for assessing and enhancing the expertise and situational awareness of emergency responders dealing with radiation crises. Through a series of expert focus group sessions using the well-established qualitative methodology of grounded theory, an Expected Mental Model State (EMMS) was developed. The methodology used an influence diagram architecture to conceptually capture and codify key areas relevant to effective emergency response. The research identifies fourteen EMMS key conceptual domains, further elaborated into 301 subtopics, providing a multi-dimensional structure for the proposed mental model framework. Three pivotal notions of mental model emerged within the EMMS framework: Knowledge Topology, Envisioning (Belief), and Response and Operability. These notions were found to align with previous theories of mental models and are vital for understanding how HAZMAT technicians conceptualize and respond to RDD incidents. The study emphasizes the critical role of mental models in enhancing preparedness and effective response strategies during radiation emergencies. The EMMS framework offers a versatile methodology that can be adapted across various kinds of emergency responders and high-risk situations, including the broader Chemical, Biological, Radiological, and Nuclear (CBRN) spectrum. Using this EMMS framework to develop an EMMS Diagnostic Matrix can provide a roadmap for identifying areas for the development of specialized training modules that have the potential to significantly elevate both the quality and efficacy of responder training and preparation.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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