UCLA

Purpose:

Estimates of the minimally important change (MIC) can be used to evaluate whether group-level differences are large enough to be important. But responders to treatment have been based upon group-level MIC thresholds, resulting in inaccurate classification of change over time. This article reviews options and provides suggestions about individual-level statistics to assess whether individuals have improved, stayed the same, or declined. Methods Review of MIC estimation and an example of misapplication of MIC group-level estimates to assess individual change. Secondary data analyses to show how perceptions about meaningful change can be used along with significance of individual change. Results MIC thresholds yield over-optimistic conclusions (i.e., classify those who have not changed as responders to treatment). Individual change statistics can be used along with individual retrospective ratings of change. Conclusions Future studies need to evaluate the significance of individual change using appropriate individual-level statistics such as the reliable change index or the equivalent coefficient of repeatability.