Sharing the knowledge gained from occupational cohort studies: A call for action
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Objectives: An immense body of knowledge has been created by establishing various job-exposure matrices (JEMs) to assess occupational exposures in community- and industry-based cohort studies. These JEMs could be made available to occupational epidemiologists using knowledge-sharing technologies, thereby saving considerable amounts of time and money for researchers investigating occupation-related research questions. In this paper, the authors give an example of how a detailed JEM can be easily transformed into a job-specific module (JSM) for use in community-based studies. Methods: OccIDEAS is operationalised as a web-based software, combining the use of JSMs with an individual expert exposure assessment to assess occupational exposures in various industries according to a set of predefined rules. The authors used a JEM focusing on endocrine-disrupting chemicals from a German study on testicular cancer in the automobile industry to create a JSM in OccIDEAS. Results: The JEM was easily translated into OccIDEAS requiring about 50 h of work by an epidemiologist familiar with the German JEM to learn about the OccIDEAS structure, establish the required set of exposure rules and to translate the JEM into OccIDEAS. Language did not represent an obstacle for translation either. To make the data available in an international context, an interpreter had to translate the German tasks and exposures after they were coded into OccIDEAS. Conclusions: JEMs which are constructed based on identifying tasks that determine exposure can be easily transformed into a JSM. Occupational epidemiologists are invited to contribute to the international scope of OccIDEAS by providing their previously established JEMs to make existing data on occupational exposures widely available to the epidemiological community.
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Florath, I.; Glass, D.; Rhazi, M.; Parent, M.; Fritschi, Lin (2018)Objectives: To estimate the inter-rater agreement between exposure assessment to asthmagens in current jobs by algorithms based on task-based questionnaires (OccIDEAS) and by experts. Methods: Participants in a cross-sectional ...
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