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The big picture on accident causation: A review, synthesis and meta-analysis of AcciMap studies.

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Title: The big picture on accident causation: A review, synthesis and meta-analysis of AcciMap studies.
Authors: Salmon, Paul M.1,2 (AUTHOR), Hulme, Adam1 (AUTHOR), Walker, Guy H.2,3 (AUTHOR), Waterson, Patrick4 (AUTHOR), Berber, Elise1 (AUTHOR), Stanton, Neville A.1,2 (AUTHOR)
Source: Safety Science. Jun2020, Vol. 126, pN.PAG-N.PAG. 1p.
Subjects: Meta-analysis, Systems theory, Accident prevention, Further education (Great Britain)
Abstract: • AcciMap is arguably the most popular accident analysis method. • We reviewed and synthesised 23 published AcciMap studies. • We identified 5587 contributory factors spanning 79 contributory factor types. • We found a set of contributory factors that often play a role in major accidents. • Further applications of our contributory factor classification scheme are encouraged. As AcciMap is now arguably the most popular accident analysis method in the peer-reviewed literature, there are key learnings to be taken from reviewing and synthesising published AcciMap analyses. In particular, the extent to which the network of contributory factors underpinning accidents is consistent across safety critical domains. This study reviewed and synthesised 23 AcciMap analyses published in the peer-reviewed literature. Contributory factors and relationships were extracted and thematically coded to form a single multi-domain, multi-incident AcciMap. The resulting AcciMap contains 5587 contributory factors spanning seventy-nine distinct contributory factor types. The findings reveal a set of generic contributory factors that consistently play a role in major accidents regardless of domain. Additionally, contributory factors previously only associated with sharp-end human operators are, in fact, prevalent across multiple levels of accident systems. The implications of these findings for accident theory and accident analysis and prevention activities are discussed. For future AcciMap analyses it is recommended that the contributory factor classification scheme developed in the present study is used to support the identification and classification of contributory factors. In addition, further education for analysts on the systems thinking perspective on accident causation is recommended. [ABSTRACT FROM AUTHOR]
Copyright of Safety Science is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 142250627
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: • AcciMap is arguably the most popular accident analysis method. • We reviewed and synthesised 23 published AcciMap studies. • We identified 5587 contributory factors spanning 79 contributory factor types. • We found a set of contributory factors that often play a role in major accidents. • Further applications of our contributory factor classification scheme are encouraged. As AcciMap is now arguably the most popular accident analysis method in the peer-reviewed literature, there are key learnings to be taken from reviewing and synthesising published AcciMap analyses. In particular, the extent to which the network of contributory factors underpinning accidents is consistent across safety critical domains. This study reviewed and synthesised 23 AcciMap analyses published in the peer-reviewed literature. Contributory factors and relationships were extracted and thematically coded to form a single multi-domain, multi-incident AcciMap. The resulting AcciMap contains 5587 contributory factors spanning seventy-nine distinct contributory factor types. The findings reveal a set of generic contributory factors that consistently play a role in major accidents regardless of domain. Additionally, contributory factors previously only associated with sharp-end human operators are, in fact, prevalent across multiple levels of accident systems. The implications of these findings for accident theory and accident analysis and prevention activities are discussed. For future AcciMap analyses it is recommended that the contributory factor classification scheme developed in the present study is used to support the identification and classification of contributory factors. In addition, further education for analysts on the systems thinking perspective on accident causation is recommended. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Safety Science is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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