Journal article
Testing the reliability of accident analysis methods: a comparison of AcciMap, STAMP-CAST and AcciNet
Ergonomics, Vol.67(5), pp.695-715
2024
PMID: 37523211
Abstract
Accident analysis methods are used to model the multifactorial cause of adverse incidents. Methods such as AcciMap, STAMP-CAST and recently AcciNet, are systemic approaches that support the identification of safety interventions across sociotechnical system levels. Despite their growing popularity, little is known about how reliable systems-based methods are when used to describe, model and classify contributory factors and relationships. Here, we conducted an intra-rater and inter-rater reliability assessment of AcciMap, STAMP-CAST and AcciNet using the Signal Detection Theory (SDT) paradigm. A total of 180 hours’ worth of analyses across 360 comparisons were performed by 30 expert analysts. Findings revealed that all three methods produced a weak to moderate positive correlation coefficient, however the inter-rater reliability of STAMP-CAST was significantly higher compared to AcciMap and AcciNet. No statistically significant or practically meaningful differences were found between methods in the overall intra-rater reliability analyses. Implications and future research directions are discussed.
Details
- Title
- Testing the reliability of accident analysis methods: a comparison of AcciMap, STAMP-CAST and AcciNet
- Authors
- Adam Hulme (Corresponding Author) - Centre for Human Factors and Sociotechnical SystemsNeville A Stanton (Author) - University of the Sunshine Coast, Queensland, Centre for Human Factors and Systems ScienceGuy H Walker (Author) - University of the Sunshine Coast, Queensland, Centre for Human Factors and Systems SciencePatrick Waterson (Author) - Loughborough UniversityPaul Salmon (Author) - University of the Sunshine Coast, Queensland, Centre for Human Factors and Systems Science
- Publication details
- Ergonomics, Vol.67(5), pp.695-715
- Publisher
- Taylor & Francis
- Date published
- 2024
- DOI
- 10.1080/00140139.2023.2240048
- ISSN
- 1366-5847
- PMID
- 37523211
- Copyright note
- This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc- nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
- Organisation Unit
- Centre for Human Factors and Systems Science
- Language
- English
- Record Identifier
- 99743098502621
- Output Type
- Journal article
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- Domestic collaboration
- International collaboration
- Web Of Science research areas
- Engineering, Industrial
- Ergonomics
- Psychology
- Psychology, Applied
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