Background and objective: To be useful, results from health-related quality of life (HRQoL) measures must be interpretable. The objective of this article is to examine statistical (distributional) approaches to interpretability. The standard error of measurement (SEM) and the standard error of the difference (S(diff)) are used in data on individuals with Parkinson's disease to calculate the minimum change scores required to be statistically meaningful for each dimension of an instrument to assess HRQoL in Parkinson's disease, the PDQ-39.
Methods: Data was collected from both a community and a clinic study; in both studies the PDQ-39 was administered at baseline and follow-up.
Results: The patterns of SEMs and S(diff)s were similar both across time periods and between samples, for all dimensions except Social Support.
Conclusions: The results suggest that, for example, six points change on a 0-100 transformed scoring of the Mobility dimension may be considered on distributional grounds a minimum meaningful change. The demonstrated consistency across occasions and types of sample of SEMs and S(diff) for the majority of the dimensions of the PDQ-39, is evidence of the theoretically claimed advantage of this measure of sample independence, and supports use of this distributional approach to minimum meaningful change.