Use of O*NET as a job exposure matrix: a literature review
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2010/09/01
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Description:BACKGROUND: O*NET is a publicly available online database that describes occupational features across US job titles and that has been used to estimate workplace physical and psychosocial exposures and organizational characteristics. The aim of this review is to describe and evaluate the use of O*NET as a job exposure matrix. METHODS: A review of the peer-reviewed published and gray literature was conducted. Twenty-eight studies were found that used O*NET to estimate work exposures related to health or safety outcomes. Each was systematically evaluated across eight main features. RESULTS: Many health outcomes have been studied with O*NET estimates of job exposures. Some studies did not use conceptual definitions of exposure; few studies estimated convergent validity, most used predictive validity. Multilevel analysis was underutilized. CONCLUSION: O*NET is worthy of exploration by the occupational health community, although its scientific value is still undetermined. More studies could eventually provide evidence of convergent validity. O*NET has the potential to allow examination of occupational risks that might have otherwise been ignored due to missing data or resource constraints on field data collection of job exposure information. [Description provided by NIOSH]
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ISSN:0271-3586
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Volume:53
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Issue:9
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NIOSHTIC Number:nn:20038882
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Citation:Am J Ind Med 2010 Sep; 53(9):898-914
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Contact Point Address:Manuel Cifuentes MD, ScD, Research Scientist, Center for Disability Research, Liberty Mutual Research Institute for Safety, 71 Frankland Road, Hopkinton, MA 01748, USA
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Email:manuel.cifuentes@libertymutual.com
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Federal Fiscal Year:2010
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Performing Organization:University of Massachusetts - Lowell
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Peer Reviewed:True
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Start Date:20000930
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Source Full Name:American Journal of Industrial Medicine
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End Date:20060929
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Main Document Checksum:urn:sha-512:870c176f4350f9714ce02b190fa5f74044122e363a5a04ac3456fb9d5ea3a9db46a025c905418a3540bb7b0f5ba85097bd2d6192eadbd37c660de566816fa54d
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