A procedure for linking psychosocial job characteristics data to health surveys.
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1988/08/01
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Description:A system was proposed in which job information from comprehensive national surveys of working conditions can be used to imput job psychosocial characteristics to surveys of health status. Earlier efforts often carry biases which become important when using linkage systems based on mean scores. The linkage system in this new method was modified to adjust imputed individual scores for age, education, race, marital status, and sex. The efficiency and reliability of the modified linkage system were reported. Decision latitude and physical exertion were more efficiently imputed with the linkage system than earnings in spite of the psychosocial nature of the earlier terms. Such as system may prove useful in initial epidemiological studies of the consequences of psychosocial job characteristics. Three cases were examined using this new method of analyses. The first was a case of simple regression of the risk of coronary heart disease on job strain or other work condition. The second case was regression of the risk of coronary heart disease on a work condition such as job strain and age. The final case involved regression of the risk of coronary heart disease on job strain, age, and a control variable such as cholesterol intake. [Description provided by NIOSH]
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ISSN:0090-0036
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Volume:78
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Issue:8
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NIOSHTIC Number:nn:00181462
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Citation:Am J Public Health 1988 Aug; 78(8):904-909
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Contact Point Address:Joseph E. Schwartz, PhD, Department of Psychiatry and Behavioral Medicine, State University of New York at Stony Brook, Stony Brook, NY 11794
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Federal Fiscal Year:1988
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Performing Organization:Columbia University, Department of Industrial Engineering and Operations Research, New York, New York
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Peer Reviewed:True
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Start Date:19790701
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Source Full Name:American Journal of Public Health
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End Date:19840731
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Main Document Checksum:urn:sha-512:c9c0c1e238dae6146563089006e599c5362bdd2be5642b17df612add1118c68c8156c8c4c200661367e1fad623ae6312d03cf4c7de17679283be14eafacc4149
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