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Association analysis of causative factors of fall from height accidents

Year: 2025
Type: article
Abstract: Working at height is widespread across various industries, with frequent and hazardous falls occurring regularly. Such tasks are often linked to multifactorial issues, where the interplay of diverse factors leads to accidents that are challenging to control effectively. This study establishes an index system for the factors influencing falls from height by statistically analyzing 101 incidents, identifying 64 causative elements classified into four categories. These include 17 factors related to operator condition and behavior, 13 concerning equipment and facility conditions, 7 pertaining to site conditions, and 27 associated with production operations management. Utilizing the Apriori algorithm and Gephi software, the study mined the association rules of causal factors in falls from height and constructed their network diagram. By examining association rules with high support, confidence, and lift, the relationships between key causal factors leading to accidents are clarified, identifying critical operational control points and providing a scientific foundation for reducing the incidence of falls from height. Currently, China's standards related to working at height remain fragmented. This study lays the foundation for the development of comprehensive, systematic, generic safety management standards for working at height, satisfying the needs of the field.
DOI: 10.1016/j.jnlssr.2025.100221
Authors: Hanjun Guo, Yuwei Mo, Fushuai Guo, Rongxue Kang, Ke Tang, Qiuju Ma
Language: English
Open Access status: gold
Estimated APC paid: $1,200
OpenAlex ID: W4411088846
FWCI: 2.605
Cites: 13
Cited by: 3
Related to: 10