Demands for multidimensional information on the work environment: A methodological framework for regular studies.

BACKGROUND: Development of methodologies for making economic decisions on designing work environment studies is a theoretical challenge for researchers in occupational health sciences. There are well-defined tools available in the relevant literature for analysis of cost-efficiency associated with t...

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Bibliographic Details
Published in:Work Vol. 63; no. 1; pp. 9 - 21
Main Author: Rezagholi, Mahmoud
Format: equations & formulas research tables/charts Journal Article
Published: Sage Publications Inc. 2019
Online Access:View this record in EBSCOhost
Description
Summary:BACKGROUND: Development of methodologies for making economic decisions on designing work environment studies is a theoretical challenge for researchers in occupational health sciences. There are well-defined tools available in the relevant literature for analysis of cost-efficiency associated with the assessment of an occupational exposure of interest. However, these analytical tools are not appropriate for holistic studies of the work environment as a multidimensional reality. OBJECTIVE: This article introduces an appropriate methodology for designing cross-sectional comprehensive studies of the work environment, in order to optimize the production of information on the psychosocial, ergonomic, and physical dimensions of the work environment in regular studies. METHODS: The employment of a translog cost-utility function is suggested as a suitable way to provide cost-minimized designs for regular studies which are aimed at providing or developing multidimensional information systems of the work environment. RESULTS: The translog cost-utility function is not subject to predetermined restrictions, but has a flexibility property allowing it to be transformed to any specification that is adaptable to the specific work environmental characteristics and research requirements. CONCLUSION: The translog cost-utility function is an appropriate econometric model for optimizing the production of multidimensional information on occupational exposures in regular cross-sectional workplace studies.