Submissions are invited for a special section of Human Factors
on classifying and understanding human error. It is generally recognized that humans have a finite set of cognitive and physical resources and that when faced with complex, target-rich environments, they can and will commit errors (Institute of Medicine, 1999; Reason, 1990). Aviation, medical, and transportation errors can be particularly costly in terms of both human life and loss of resources. In an effort to improve safety, these and other industries
are developing and implementing systems to identify and classify human error and the factors that contribute to human error. The goal of these systems is to identify the causal factors of human error and to reduce or eliminate those factors.
There are a number of challenges associated with organizing human error. For example, the typical aviation voluntary incident reporting system requires contributors to submit text narrative describing the incident. However, in order to identify trends, analysts must read the narratives individually and classify them into groups by causal factor. This type of analysis is time consuming
and does not allow for comparison of data across programs within an industry (e.g., Flight Operational Quality Assurance data and Aviation Safety Action Program data), across specific organizations within an industry, or across industries (aviation and maritime). Consequently, when these data have been analyzed for statistical trends, the process has been inefficient.
This special section is intended to bring together the research of individuals and organizations and to highlight their successes and challenges in organizing and understanding human error. Highlights would include the development of human error taxonomies or classification schemes for factors contributing to human error and the analysis of data from such schemes. We hope that this special section will provide valuable information to the user community regarding current best practices in this area. Manuscripts submitted may be empirical works describing research conducted to organize human error or human factors contributions to error, the development or implementation of human error reporting systems (e.g., accident or incident reporting systems),
taxonomies or classification schemes for organizing human error or contributors to human error, or the analysis of data from these systems. Theoretical works regarding the development of human error taxonomies or classification schemes for organizing contributors to human error are also encouraged.
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