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Dynamic Decision Making in Mine Emergency Situations—Existing Collection in use without an OMB control number—National Institute for Occupational Safety and Health (NIOSH), Centers for Disease Control and Prevention (CDC).
Background and Brief Description
Mining is a context filled with tragic outcomes, as thousands of miners die in mining accidents each year throughout the world. In the process of examining workers' responses in emergency situations in mines, researchers at the NIOSH-Pittsburgh Research Laboratory (PRL) have found that one of the key human behavior processes that need to be better understood to better handle emergency situations is Decision Making (Vaught, Brnich, & Mallett, 2004). Decision Making, the process by which alternatives are constructed and a choice is made, continues to be one of the critically understudied aspects of mine emergencies. For example, The Mine Safety Technology and Training (MSTT) Commission suggests that escape/rescue decision-making is one of the most critical skill/knowledge gaps identified in mining (MSTTC, 2006). Their report strongly supports the need for additional training in decision-making during emergency situations to improve the ability of miners to escape (or be rescued).
The research proposed here will help address this gap by integrating the theoretical knowledge of human decision making in dynamic situations with the practical aspects of training miners. The research will result in the improved science of decision making and practical guidelines and tools that demonstrate how to best train decision making in the unique conditions of accidents when under workload, uncertainty, and time constraints.
A simple Decision Making Game (DMGame) was used in a laboratory study to investigate choice strategies based on the dynamic development of cues. Through a contract with the Centers for Disease Control and Prevention (Contract #200-2009-31403), the Dynamic Decision Making Laboratory at Carnegie Mellon University will investigate several independent variables relevant to Instance-Based Learning Theory, including: the diversity of instances, the number of instances (base rates) needed to improve accuracy in the triage process, and the effects of time constraints and workload on the effectiveness of triage. The manipulation of these independent variables will reveal training scenarios and conditions that are more effective during learning and at transfer. Knowledge acquired during training will be tested in transfer conditions. The transfer conditions will vary depending on the participants used in the Start Printed Page 51983experiment. New guidelines for training for unexpected situations will be developed from the results of the laboratory experiment. The results and guidelines will be published in journal research papers and presented in international conferences and meeting.
The Dynamic Decision Making Laboratory conducted this research with a total of 28 students from Carnegie Mellon University and the University of Pittsburgh between January 2010 and December 2010. Participants were recruited through an online research participant pool from Carnegie Mellon University and the University of Pittsburgh to participate in a simple DMGame, called the “Work Hazard Game.” Participants were asked to read and sign a consent form. After signing the form, participants were provided with instructions on how to play the game. They then completed the Work Hazard Game. Overall, participation lasted about 30 minutes. The game recorded participants' actions and the data was transferred to statistical software (i.e., SPSS) for analysis. There were no costs to respondents other than their time. The total estimated annual burden hours are 14.
|Respondents for DM Game||Number of respondents||Number of responses per respondent||Average burden per response (in hours)|
Dated: August 15, 2011.
Reports Clearance Officer, Centers for Disease Control and Prevention.
[FR Doc. 2011-21200 Filed 8-18-11; 8:45 am]
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