Variable definitions and distributions of exposure data from a consortium study on carpal tunnel syndrome
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2015/09/01
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Details
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Personal Author:Bao SS ; Burt, Susan E. ; Dale, Ann M. ; Evanoff BA ; Garg, Arun ; Gerr FE ; Harris-Adamson C ; Hegmann KT ; Kapellusch JM ; Merlino LA ; Rempel DM ; Silverstein BA ; Thiese MS
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Description:Insufficient sample size causes lower statistical power that may hinder findings of relationships between occupational physical exposures and musculoskeletal disorders. To solve this problem, researchers often want to pool data with similar study designs together to increase the statistical power. However, a recent consortium study on the relationships between physical exposures and Carpal Tunnel Syndrome (CTS) found that due to slight differences in variable definitions, data collection procedures, data processing approaches, and data analysis methods, pooling data from multiple studies can be challenging. Using data independently collected by six research groups in 54 US workplaces in 10 US States, this paper presents some of the challenges in data pooling, and final selections of comparable variables. Distributions of the selected exposure data of 3010 subjects and variable definitions are presented. [Description provided by NIOSH]
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ISSN:1071-1813
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Place as Subject:California ; Iowa ; Missouri ; Ohio ; OSHA Region 10 ; OSHA Region 5 ; OSHA Region 7 ; OSHA Region 8 ; OSHA Region 9 ; Utah ; Washington ; Wisconsin
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Volume:59
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NIOSHTIC Number:nn:20048557
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Citation:Proceedings of the Human Factors and Ergonomics Society 59th Annual Meeting, October 26-30, 2015, Los Angeles, California. Santa Monica, CA: Human Factors and Ergonomics Society, 2015 Sep; 59:1239-1242
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Federal Fiscal Year:2015
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Performing Organization:University of California-San Francisco
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Peer Reviewed:True
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Start Date:20100901
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Source Full Name:Proceedings of the Human Factors and Ergonomics Society 59th Annual Meeting, October 26-30, 2015, Los Angeles, California
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End Date:20140831
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Main Document Checksum:urn:sha-512:1852409de6377e861a3ecfcf9c1c46183a0ec864797da0928aa5dcb770b7c8a8739a1b5de945049dcfcae38447998b2c418252f617ae82d9cd70227948e598d4
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