Data processing costs for three posture assessment methods

Abstract

Background: Data processing contributes a non-trivial proportion to total research costs, but documentation of these costs is rare. This paper employed a priori cost tracking for three posture assessment methods (self-report, observation of video, and inclinometry), developed a model describing the fixed and variable cost components, and simulated additional study scenarios to demonstrate the utility of the model. Methods. Trunk and shoulder postures of aircraft baggage handlers were assessed for 80 working days using all three methods. A model was developed to estimate data processing phase costs, including fixed and variable components related to study planning and administration, custom software development, training of analysts, and processing time. Results: Observation of video was the most costly data processing method with total cost of 30,630, and was 1.2-fold more costly than inclinometry ( 26,255), and 2.5-fold more costly than self-reported data ( 12,491). Simulated scenarios showed altering design strategy could substantially impact processing costs. This was shown for both fixed parameters, such as software development and training costs, and variable parameters, such as the number of work-shift files processed, as well as the sampling frequency for video observation. When data collection and data processing costs were combined, the cost difference between video and inclinometer methods was reduced to 7%; simulated data showed this difference could be diminished and, even, reversed at larger study sample sizes. Self-report remained substantially less costly under all design strategies, but produced alternate exposure metrics. Conclusions: These findings build on the previously published data collection phase cost model by reporting costs for post-collection data processing of the same data set. Together, these models permit empirically based study planning and identification of cost-efficient study designs. © 2013 Trask et al.; licensee BioMed Central Ltd.