ArticleEpidemiology and health2019
Analysis of the severity of occupational injuries in the mining industry using a Bayesian network.
Article in Epidemiology and health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.
- Active learning and sector-specific simulations mitigate the first-month injury risk in young workers.Frontiers in public health · 2026Pooled it
- Global prevalence of occupational injuries among sanitation workers: a systematic review and meta-analysis.Frontiers in public health · 2024Pooled it
- Human reliability analysis in maintenance and repair operations of mining trucks: A Bayesian network approach.Heliyon · 2024Article
- Resilience, job satisfaction, occupational stress, and occupational accidents among healthcare professionals: A Bayesian network analysis.Work (Reading, Mass.) · 2024Article
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Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesOccupational 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.
methodsThe 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.
resultsBased 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.
conclusionsAmong 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.