- Title
- Bridging the research-practice gap: Validity of a software tool designed to support systemic accident analysis by risk managers
- Creator
- Goode, Natassia; Salmon, Paul; Taylor, Natalie; Lenné, Michael; Finch, Caroline
- Date
- 2015
- Type
- Text; Conference proceedings
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/98819
- Identifier
- vital:10293
- Identifier
-
https://doi.org/10.1007/978-3-319-20373-7_20
- Abstract
- Despite the proposed advantages of systems accident analysis (SAA) methods for understanding incident-causation, these approaches have not been widely adopted by practitioners. This represents a significant gap between research and practice in accident analysis. The Understanding and Preventing Led Outdoor Accidents Data System (UPLOADS) provides a series of tools to address this gap. The aim of this study was to evaluate the validity of UPLOADS by comparing analyses generated by risk managers and researchers experienced in SAA. Twenty-three risk managers used UPLOADS to collect and analyse incident data from their organization over a three month period. The reports were then analyzed by two researchers experienced in SAA, and compared to those generated by participants. Participants identified half the number of factors identified by researchers, and tended to focus on only one or two factors as the causes of each incident. The potential consequences for practitioners' understanding of incident-causation and countermeasure development are discussed, as well as ways of improving the system. © Springer International Publishing Switzerland 2015.
- Publisher
- Springer Verlag
- Relation
- http://purl.org/au-research/grants/nhmrc/1058737
- Rights
- Copyright © Springer International Publishing Switzerland 2015.
- Rights
- This metadata is freely available under a CCO license
- Subject
- 08 Information and Computing Sciences; Accident analysis; Research translation; Systems thinking; Accident prevention; Ergonomics; Human computer interaction; Risk assessment; Risk management; Data systems; Incident data; Number of factors; Risk analysis
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