title: Statistical power and measurement allocation in ergonomic intervention studies assessing upper trapezius EMG amplitude. A case study of assembly work.
abstract: The present study aimed at exploring the statistical power of ergonomic intervention studies using electromyography (EMG) from the upper trapezius muscle. Data from a previous study of cyclic assembly work were reanalyzed with respect to exposure variability between subjects, between days, and within days. On basis of this information, the precision and power of different data collection strategies were explored. A sampling strategy comprising four registrations of about two min each (i.e. two work cycles) for one day per subject resulted in coefficients of variation between subjects on the 10-, 50-, and 90-APDF-percentiles of 0.44, 0.31, and 0.29, respectively. The corresponding necessary numbers of subjects in a study aiming at detecting a 20% exposure difference between two independent groups of equal size were 154, 78, and 68, respectively (p< or = 0.05, power 0.80). Multiple measurement days per subject would improve power, but only to a marginal extent beyond 4 days of recording. Increasing the number of recordings per day would have minor effects. Bootstrap resampling of the data set revealed that estimates of variability and power were associated with considerable uncertainty. The present results in combination with an overview of other occupational studies showed that common-size investigations using trapezius EMG percentiles are at great risk of suffering from insufficient statistical power, even if the expected intervention effect is substantial. The paper suggests a procedure of how to retrieve and use exposure variability information as an aid when studies are planned, and how to allocate measurements efficiently.
authors.affiliation: Division of Production Ergonomics, School of Technology and Society, Malmö University, SE-20506 Malmö, Sweden. svend.erik.mathiassen@ts.mah.se
authors.forename: Svend Erik
authors.initials: SE
authors.lastname: Mathiassen
authors.forename: Alex
authors.initials: A
authors.lastname: Burdorf
authors.forename: Allard J
authors.initials: AJ
authors.lastname: van der Beek
mesh_terms: D003627:Data Interpretation, Statistical; D004576:Electromyography; D006804:Ergonomics / Q000379:methods*; D005260:Female; D006801:Humans; D007221:Industry; D008297:Male; D009119:Muscle Contraction / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D009333:Neck / Q000502:physiology; D009784:Occupational Diseases / Q000453:epidemiology*; D012107:Research Design; D012782:Shoulder / Q000502:physiology*; D013647:Task Performance and Analysis