ArticleJournal of exposure science & environmental epidemiology2017
Developing a job-exposure matrix with exposure uncertainty from expert elicitation and data modeling.
Article in Journal of exposure science & environmental epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Occupational exposures and genetic susceptibility to occupational exposures are related to sickness absence in the Lifelines cohort study.Scientific reports · 2020Trial
- Bayesian Hierarchical Framework from Expert Elicitation in the South African Coal Mining Industry for Compliance Testing.International journal of environmental research and public health · 2023Article
- Parental occupational exposure and congenital heart diseases in a Hungarian case-control study.International archives of occupational and environmental health · 2021Article
- Development of Job Exposure Matrices to Estimate Occupational Exposure to Solar and Artificial Ultraviolet Radiation.Annals of work exposures and health · 2020Article
- Development of a Job-Exposure Matrix for Assessment of Occupational Exposure to High-Frequency Electromagnetic Fields (3 kHz-300 GHz).Annals of work exposures and health · 2019Article
- The long-term health consequences of genocide: developing GESQUQ - a genocide studies checklist.Conflict and health · 2019Article
- Job exposure matrix for electric shock risks with their uncertainties.International journal of environmental research and public health · 2015Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Job exposure matrices (JEMs) are tools used to classify exposures for job titles based on general job tasks in the absence of individual level data. However, exposure uncertainty due to variations in worker practices, job conditions, and the quality of data has never been quantified systematically in a JEM. We describe a methodology for creating a JEM which defines occupational exposures on a continuous scale and utilizes elicitation methods to quantify exposure uncertainty by assigning exposures probability distributions with parameters determined through expert involvement. Experts use their knowledge to develop mathematical models using related exposure surrogate data in the absence of available occupational level data and to adjust model output against other similar occupations. Formal expert elicitation methods provided a consistent, efficient process to incorporate expert judgment into a large, consensus-based JEM. A population-based electric shock JEM was created using these methods, allowing for transparent estimates of exposure.
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Registered trials
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