-
Analysis of the severity of occupational injuries in the mining industry using a Bayesian network
-
Mostafa Mirzaei Aliabadi, Hamed Aghaei, Omid kalatpuor, Ali Reza Soltanian, Asghar Nikravesh
-
Epidemiol Health. 2019;41:e2019017. Published online May 11, 2019
-
DOI: https://doi.org/10.4178/epih.e2019017
-
-
11,623
View
-
232
Download
-
11
Web of Science
-
7
Crossref
-
 Abstract
 PDF
-
Abstract
OBJECTIVES
Occupational injuries are known to be the main adverse outcome of occupational accidents. The purpose of the current study was to identify control strategies to reduce the severity of occupational injuries in the mining industry using Bayesian network (BN) analysis.
METHODS The BN structure was created using a focus group technique. Data on 425 mining accidents was collected, and the required information was extracted. The expectation-maximization algorithm was used to estimate the conditional probability tables. Belief updating was used to determine which factors had the greatest effect on severity of accidents.
RESULTS Based on sensitivity analyses of the BN, training, type of accident, and activity type of workers were the most important factors influencing the severity of accidents. Of individual factors, workers’ experience had the strongest influence on the severity of accidents.
CONCLUSIONS Among the examined factors, safety training was the most important factor influencing the severity of accidents. Organizations may be able to reduce the severity of occupational injuries by holding safety training courses prepared based on the activity type of workers.
-
Summary
-
Citations
Citations to this article as recorded by  - A fuzzy Bayesian network DEMATEL model for predicting safety behavior
Mohsen Mahdinia, Iraj Mohammadfam, Ahmad Soltanzadeh, Mostafa Mirzaei Aliabadi, Hamed Aghaei
International Journal of Occupational Safety and Ergonomics.2023; 29(1): 36. CrossRef - Analysis of occupational accidents among nurses working in hospitals based on safety climate and safety performance: a Bayesian network analysis
Fakhradin Ghasemi, Hamed Aghaei, Taleb Askaripoor, Farhad Ghamari
International Journal of Occupational Safety and Ergonomics.2022; 28(1): 440. CrossRef - Retrospective assessment of the association between noise exposure and nonfatal and fatal injury rates among miners in the United States from 1983 to 2014
Abas Shkembi, Lauren M. Smith, Richard L. Neitzel
American Journal of Industrial Medicine.2022; 65(1): 30. CrossRef - Contributing effects of individual characteristics, behavioural and job-related factors on occurrence of mining-related injuries: A systematic review
Michael Mayom Ajith, Apurna Kumar Ghosh, Janis Jansz
Work.2022; 71(1): 87. CrossRef - Human Error Analysis for Hydraulic Engineering: Comprehensive System to Reveal Accident Evolution Process with Text Knowledge
Dan Tian, Hao Liu, Shu Chen, Mingchao Li, Chengzhao Liu
Journal of Construction Engineering and Management.2022;[Epub] CrossRef - Analysis of occupational accidents in Spain using shrinkage regression methods
Vicente Gallego, Ana Sánchez, Isabel Martón, Sebastián Martorell
Safety Science.2021; 133: 105000. CrossRef - Research trends in mining accidents study: A systematic literature review
Siti Noraishah Ismail, Azizan Ramli, Hanida Abdul Aziz
Safety Science.2021; 143: 105438. CrossRef
|
KSE
