Statistical precision of categorical PATH observations of trunk posture

Abstract

Background: Field studies assessing biomechanical occupational exposures frequently utilize direct observation. PATH (Postures, Activities, Tools, and Handling) is a tool for systematically observing occupational exposures during non-cyclic or long, irregular-cycle jobs. While PATH has been used in many studies, its statistical performance under different data collection strategies has not yet been investigated. The purpose of the current study was to examine this issue. Methods: Data from labourers performing the four tasks comprising a ‘Jacking Pit Construction’ operation was extracted from a previously collected data set. Using a probability based re-sampling bootstrap approach, categorical trunk posture exposure data was compared across nine simulated data collection strategies. Results/Conclusion: At the operational level, dispersion curves showed consistent trends of increased precision with increased sizes of the data set and curves tended to intersect at the expected value seen in the parent data set. At the task level, curves did not always follow the predicted pattern, highlighting the potential pitfalls of using PATH for infrequent tasks and the striking effect that individual workers can have on group exposure estimates of such tasks.