title: A reliability and usability study of TRACEr-RAV: the technique for the retrospective analysis of cognitive errors--for rail, Australian version.
abstract: The aim of this study was to compare the usability and reliability of two human error identification tools: TRACEr-Rail (developed by the Rail Safety and Standards Board in the UK) and TRACEr-RAV (an Australian specific version of the tool). Following an attempt to modify TRACEr-Rail to more appropriately suit the Australian rail context, it was predicted that TRACEr-RAV would be rated as more usable and be applied more consistently by Australian users than TRACEr-Rail. In Experiment 1, twenty-five rail employees used either TRACEr-Rail or TRACEr-RAV1 to extract and classify errors from six Australian rail incident reports. In Experiment 2, eleven university students used both TRACEr-Rail and TRACEr-RAV2 to extract and classify errors from three incident summaries. The results revealed that although modification of TRACEr-Rail to become TRACEr-RAV1 and TRACEr-RAV2 did not result in improved inter-rater reliability, modification resulted in improved ratings of usability in Experiment 2. Most participants in Experiment 2 preferred TRACEr-RAV2 to TRACEr-Rail. The poor inter-rater reliability observed was most likely the result of inadequate training, limited practice in using the tools, and insufficient human factors knowledge.
authors.affiliation: School of Risk and Safety Sciences, The University of New South Wales, Sydney, NSW 2052, Australia. m.baysari@unsw.edu.au
authors.forename: Melissa T
authors.initials: MT
authors.lastname: Baysari
authors.forename: Carlo
authors.initials: C
authors.lastname: Caponecchia
authors.forename: Andrew S
authors.initials: AS
authors.lastname: McIntosh
mesh_terms: D000059:Accidents / Q000145:classification / Q000523:psychology*; D000328:Adult; D001315:Australia; D003071:Cognition; D005260:Female; D006801:Humans; D008297:Male; D015588:Observer Variation; D011890:Railroads / Q000592:standards; D015203:Reproducibility of Results; D013647:Task Performance and Analysis; D000078329:Workforce