Systematic working environment efforts require regular assessment of the risk of ill health, with emphasis on the quantitative measurement data (i.e., figures) for, e.g., working postures, physical exertion and work-cycle duration.
Researchers also need reliable data on physical strain for their studies concerning the relationship between strain and health in order to be able to evaluate the effect of changes. The reliability of a measurement strategy for physical strain depends on the variability in strain in the individual and from person to person, the variability caused by the actual method of measurement, and the variability of each piece of information and when compared to other information. For relatively simple measurement structures and under a number of statistical conditions, the relationship between these factors and the performance of the measurement strategy is described with the use of simple mathematical functions, if the size of the data sample is known. For more complicated measurement proceedings, however, or when the data sample infringes the statistical conditions, it is difficult to evaluate the performance. This results in difficulty in assessing the quality of the results and in planning measurement strategies in a new study in accordance with the quality requirements placed on the study.
The idea behind this framework project, spread out over several years, is to develop principles for the assessment of the statistical performance of data collection in field studies with different instruments of measurement and different measurement strategy designs to enable the establishment and interpretation of concrete strategies for data collection.