Statistical performance of observational work sampling for assessment of categorical exposure variables: a simulation approach illustrated using PATH data

The Annals of Occupational Hygiene
Svend Erik MathiassenLaura Punnett

Abstract

Observational work sampling is often used in occupational studies to assess categorical biomechanical exposures and occurrence of specific work tasks. The statistical performance of data obtained by work sampling is, however, not well understood, impeding informed measurement strategy design. The purpose of this study was to develop a procedure for assessing the statistical properties of work sampling strategies evaluating categorical exposure variables and to illustrate the usefulness of this procedure to examine bias and precision of exposure estimates from samples of different sizes. From a parent data set of observations on 10 construction workers performing a single operation, the probabilities were determined for each worker of performing four component tasks and working in four mutually exclusive trunk posture categories (neutral, mild flexion, severe flexion, twisted). Using these probabilities, 5000 simulated data sets were created via probability-based resampling for each of six sampling strategies, ranging from 300 to 4500 observations. For each strategy, mean exposure and exposure variability metrics were calculated at both the operation level and task level and for each metric, bias and precision were assessed acro...Continue Reading

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Citations

Dec 18, 2014·The Annals of Occupational Hygiene·Noah S Seixas
Jun 26, 2014·Journal of Advanced Nursing·Nicole BlayMichael Roche

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Software Mentioned

MatLab
EST
Back Exposure Sampling Tool (
- EST )
Back
PATH
Ovako

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