Literature DB >> 22939287

Predictive models of safety based on audit findings: Part 1: Model development and reliability.

Yu-Lin Hsiao1, Colin Drury, Changxu Wu, Victor Paquet.   

Abstract

This consecutive study was aimed at the quantitative validation of safety audit tools as predictors of safety performance, as we were unable to find prior studies that tested audit validity against safety outcomes. An aviation maintenance domain was chosen for this work as both audits and safety outcomes are currently prescribed and regulated. In Part 1, we developed a Human Factors/Ergonomics classification framework based on HFACS model (Shappell and Wiegmann, 2001a,b), for the human errors detected by audits, because merely counting audit findings did not predict future safety. The framework was tested for measurement reliability using four participants, two of whom classified errors on 1238 audit reports. Kappa values leveled out after about 200 audits at between 0.5 and 0.8 for different tiers of errors categories. This showed sufficient reliability to proceed with prediction validity testing in Part 2.
Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

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Year:  2012        PMID: 22939287     DOI: 10.1016/j.apergo.2012.07.010

Source DB:  PubMed          Journal:  Appl Ergon        ISSN: 0003-6870            Impact factor:   3.661


  1 in total

1.  Risk Factors Identification of Unsafe Acts in Deep Coal Mine Workers Based on Grounded Theory and HFACS.

Authors:  Li Yang; Xue Wang; Junqi Zhu; Zhiyuan Qin
Journal:  Front Public Health       Date:  2022-03-17
  1 in total

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