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- Mathiassen, Svend Erik, et al.
(author)
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The ability of limited exposure sampling to detect effects of interventions that reduce the occurrence of pronounced trunk inclination
- 2010
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In: Applied Ergonomics. - : Elsevier BV. - 0003-6870 .- 1872-9126. ; 41:2, s. 295-304
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Journal article (peer-reviewed)abstract
- Ergonomics interventions often focus on reducing exposure in those parts of the job with the highest exposure levels, while leaving other parts unattended. A successful intervention will thus change the form of the job exposure distribution. This disqualifies standard methods for assessing the ability of various exposure measurement strategies to correctly detect the intervention effect on mean job exposure. This study used a non-parametric simulation procedure to evaluate the relationship between the number of measurements collected during a self-paced manufacturing job undergoing ergonomics interventions of varying effectiveness and the probability of correctly determining whether and to which extent the interventions reduced the overall occurrence of trunk flexion. Sixteen video-recordings taken at random times on multiple days for each of 3 workers were used to estimate the time distribution of each worker's exposure to trunk flexion of at least 20°. Nine ergonomics intervention scenarios were simulated in which the upper 1/8, 1/4, and 1/2 of the exposure distribution was reduced by 10%, 30% and 50%. Ten exposure measurement strategies were explored, collecting from 1 to 10 pre- and post-intervention exposure samples. For each worker, intervention scenario and sampling strategy, data were bootstrapped from the measured (pre-intervention) and simulated (post-intervention) exposure distributions to develop empirical data of the estimated intervention effect. Results showed that for the one to three most effective intervention scenarios, depending on worker, one to four pre- and post-intervention exposure samples were sufficient to reach an 80% probability of detecting that the intervention did, indeed, have an effect. However, even for these effective scenarios, seven or more samples were needed to obtain a probability larger than 50% of estimating the magnitude of the intervention effect to within ±50% of its true size. For less effective interventions, limited exposure sampling led to low probabilities of detecting any intervention effect, let alone its correct size.
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